Cost
$3.26per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at max effort.
GPT Astra model by OpenAI
GPT-6 Astra
OpenAI's highest-capability GPT-6 release for complex end-to-end work.
Where it sits in OpenAI's lineup
- GPT TerraOpenAI's fast, efficient GPT tier for visual reasoning, computer use, and writing.GPT-6.1 Terra
- GPT SolOpenAI's GPT model tier for demanding everyday and agentic work.GPT-6.1 Sol
- GPT LunaOpenAI's most efficient GPT model tier for focused, high-volume tasks.GPT-6 Luna
- GPT AstraOpenAI's highest-capability GPT model tier.This model
- GPT-5OpenAI's GPT-5 frontier models, released before the Sol, Terra and Luna tiers.GPT-5.5
- gpt-ossOpenAI's open-weight GPT models under the Apache 2.0 license.gpt-oss-120b
- GPT CodexOpenAI's GPT models tuned for agentic coding in Codex.GPT-5.3-Codex
- Stack role
- Foundation Model / Reasoning Engine
- Offered in
- 6 products
- Made by
- OpenAI
- Family
- GPT Astra, version 6
- Released
- Sep 3, 2026 Current
- In its family
- The only GPT Astra release we track.
Strengths and weaknesses
Compare with other models Up to 3 beside GPT-6 Astra
- GPT-6 Astra
Suggested comparisons
The models a buyer weighs against GPT-6 Astra, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside GPT-6 Astra.
GPT-6 Astra
Among the 40 current releases on this chart, GPT-6 Astra ranks first of 28 on Math, second of 24 on Science and second of 24 on Multimodal. Computer use is Meta's run on OSWorld 2.1, marked on the chart. Instruction following: not yet published by OpenAI or any independent evaluator, checked Nov 2, 2026.
Each axis is one public benchmark at one setting, on its own fixed 0 to 100 scale, so adding a model never moves another. A dotted bridge crosses a missing result, which is never a zero. A hollow mark is a result from another source: the maker's own figure or another lab's run, where the benchmark's usual source has not tested the model yet. The readout names it.
On the chart
- GPT-6 AstraThis pageResults on 11 of 12 axes$10 / $50For prompts under 272K tokens; $20 / $75 at 272K or more, as OpenRouter lists it.71 tokens/sFirst token in 269 s
Prices and speeds read between Oct 26, 2026 and Oct 28, 2026.
GPT-6 Astra on each axis11 of 12 with a result
The share of Terminal-Bench 4.0's long terminal tasks the model finishes on its own: services, kernels, proofs and data pipelines, graded on the final artifact with no partial credit.
Terminal-Bench 4.0, pass@1 averaged over 3 runs, mini-swe-agent harness
- GPT-6 Astra59.6%Vals.ai ranked it 4th on its leaderboard of Oct 24, 2026.
The share of SciCode's scientific programming subproblems the model's code solves on the first attempt.
SciCode, subproblem accuracy, pass@1, highest effort run
- GPT-6 Astra56.5%
The share of FrontierMath's held-out research-grade problems (tiers 1 to 3) the model answers correctly.
FrontierMath Tiers 1-3, accuracy, pass@1, highest effort run
- GPT-6 Astra93.7%
The share of GPQA Diamond's graduate-level biology, chemistry and physics questions the model answers correctly.
GPQA Diamond, accuracy, pass@1, highest effort run
- GPT-6 Astra95.8%
The share of Humanity's Last Exam's 2,158 text-only questions, expert-written at the edge of human knowledge, the model answers correctly without tools.
Humanity's Last Exam, accuracy, text-only questions, no tools
- GPT-6 Astra54.7%
The share of each AutomationBench task's objectives the model completes by calling REST APIs across simulated business apps (Gmail, Sheets, Slack, Salesforce, Zendesk, Jira, HubSpot), averaged over tasks. A task that breaks one of its policy guardrails scores zero.
AutomationBench-AA, score, Artificial Analysis run
- GPT-6 Astra68.5%
How much of each OSWorld 2.1 workflow the model completes by operating a real Ubuntu desktop through screenshots, mouse and keyboard: all 108 long tasks across apps, files, mail and browsers, on the September 2026 v2.1 release of the task files. A point is the mean share of each task's weighted checks the model passes (the partial score, as a percentage). The OSWorld team's own runs come first. Where the team has not run a release, the point is another lab's run or the maker's own published figure, marked with who ran it and the benchmark it ran: OSWorld 2.1 in the maker's harness, OSWorld 2.0's offline set or the earlier OSWorld-Verified. Those points are drawn so the release has a figure, and they are not ranked against the team's runs.
OSWorld 2.1, partial score, full 108-task set, v2.1 release
- GPT-6 Astra75.8%Meta's runMeta's run of GPT-6 Astra at max effort in its own test framework on all 108 tasks: the average partial score. It fully completed 34.3% of tasks.
The share of AA-LCR's questions the model answers correctly by reasoning across long sets of real documents, about 100K tokens each.
AA-LCR v1.1, accuracy, Artificial Analysis run
- GPT-6 Astra80.7%
The share of MMMU-Pro's college-level questions over charts, diagrams and photos the model answers correctly.
MMMU-Pro, overall accuracy, no tools
- GPT-6 Astra86.9%
The share of AA-Omniscience's 6,000 knowledge questions across 42 economically relevant topics the model answers correctly from memory, without search.
AA-Omniscience Accuracy, accuracy, Artificial Analysis run
- GPT-6 Astra61.6%Hallucination rate 49.8% in the same run (lower is better)
The share of SpeechMap's 2,120 sensitive and controversial but legal requests the model answers in full: arguments, essays and explanations on contested themes in politics, religion, race, sex, history and similar topics, four wordings per theme across 530 themes. SpeechMap's judge rates each response complete, evasive (hedged or redirected), a denial, or an error (the provider's API blocked the request). Only complete answers count, so the point is the share answered in full: 100 minus the share hedged, refused or blocked by the provider. Higher means more lawful requests answered in full. The share blocked at the provider is printed apart in the table, because an API error is not the model declining. Where SpeechMap runs a release both with reasoning off and with reasoning on (a -reasoning or -thinking entry), the reasoning-on entry is used; a release with one entry uses that entry.
SpeechMap, % Complete over 2,120 contested requests, reasoning-on entry
- GPT-6 Astra68.2%Reasoning cannot be turned off on this model. SpeechMap counted 21.7% of requests denied and 10.0% evaded.0.1% of requests failed at the provider and count against it
The share of MultiChallenge's multi-turn conversations in which the model keeps every instruction it was given earlier in the conversation.
MultiChallenge, accuracy, Scale AI run
- GPT-6 AstraNot yet published by OpenAI or any independent evaluator, checked Nov 2, 2026
Cost, speed, capacity, quality and accuracy for GPT-6 Astra, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
66tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 381 s
- Whole answer
- 389 s
Capacity
1.05Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 128K
- Reads
- Text, Images
Quality
52.7of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,584 Elo
- Terminal-Bench 4.0
- 59.1%
- Epoch Capabilities Index
- 169
Hallucination
49.8%wrong when it should say “I don’t know”
Hallucination rate. Of the questions it can't get right, how often it answers anyway. Lower is better. Run at max effort.
- Knowledge accuracy
- 61.6%
Where you can get it
10of 19 routes
Routes offering it. Of the clouds, gateways and coding products GILD tracks, those offering it today.
- Open weights
- No
- Licence
- OpenAI Services Agreement
Figures from Artificial Analysis, OpenAI, Epoch AI and GILD's route matrix, read Oct 26 to Nov 1, 2026. Each measure's definition and source open under . Not yet published for GPT-6 Astra: Cached input.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | GPT-6 Astra | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness. Vals.ai ranked it 4th on its leaderboard of Oct 24, 2026. | 59.6% | GPT-6 AstraEffort: not published. Harness: mini-swe-agent. | Vals.ai | Oct 24, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 56.5% | GPT-6 Astra (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 93.7% | Effort: max. Harness: none. | Epoch AI | Aug 30, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 95.8% | Effort: max. Harness: none. | Epoch AI | Aug 30, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 54.7% | GPT-6 Astra (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | 68.5% | GPT-6 Astra (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness. | Artificial Analysis | Oct 28, 2026 |
| Computer use | OSWorld 2.1Partial score, full 108-task set, v2.1 release. Meta's run of GPT-6 Astra at max effort in its own test framework on all 108 tasks: the average partial score. It fully completed 34.3% of tasks. | 75.8% | GPT-6 Astra (max)Effort: max. Harness: Meta common evaluation framework.Not drawn: OpenAI 73.5% in its maker's own harness, Sep 29, 2026. SourceNot drawn: OpenAI 72.6% in its maker's own harness, Sep 3, 2026. SourceNot drawn: OpenAI 80.9% in its maker's own harness, Oct 26, 2026. Source | MetaRun by Meta | Oct 12, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 80.7% | GPT-6 Astra (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 86.9% | GPT-6 Astra (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 61.6%Hallucination rate 49.8% in the same run (lower is better) | GPT-6 Astra (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. Reasoning cannot be turned off on this model. SpeechMap counted 21.7% of requests denied and 10.0% evaded. | 68.2%0.1% of requests failed at the provider and count against it | Effort: reasoning on. Harness: none. | SpeechMap.AI | Oct 27, 2026 |
| Instruction following | MultiChallengeAccuracy, Scale AI run | Not yet published by OpenAI or any independent evaluator, checked Nov 2, 2026 |
Price and speed
- GPT-6 Astra lists at $10 per million input tokens and $50 per million output tokens. For prompts under 272K tokens; $20 / $75 at 272K or more, as OpenRouter lists it. OpenAI pricing, Oct 26, 2026.
- GPT-6 Astra, at max effort, writes 71 output tokens per second on OpenAI's API, and its first token arrives 269 s after the request. Artificial Analysis, Oct 28, 2026.
- Fastest on the chart is the shortest time to a 500-token answer: time to first token plus 500 tokens at the median output speed.
Every model with a result, axis by axis
57 models. A maker's own figure and another lab's run are marked with their benchmark; a missing result reads "Not yet published", never zero.
| Model | Agentic coding | Code | Math | Science | Hard reasoning | Tool use | Computer use | Long context | Multimodal | Factuality | Answers in full | Instructions |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GPT-6 Astra | 59.6% | 56.5% | 93.7% | 95.8% | 54.7% | 68.5% | 75.8%Run by Meta | 80.7% | 86.9% | 61.6% | 68.2% | Not yet published |
| ||||||||||||
| GPT-6.1 Terra | 49.5% | 55.1% | 90.9% | 94.3% | 46.2% | 60.2% | 74.2%Reported by OpenAIOSWorld 2.1 | 82.7% | 84.7% | 47.6% | Not yet published | 74.2% |
| ||||||||||||
| GPT-6.1 Sol | 55.1% | 54.2% | 93.7% | 95.4% | 52.9% | 64.9% | 78%Reported by OpenAIOSWorld 2.1 | 83% | 86% | 61.8% | 69.5% | 82% |
| ||||||||||||
| GPT-6 Luna | 13.6% | 54.6% | 78.9% | 90.5% | 38.5% | 53.2% | 48.9%Run by AnthropicOSWorld 2.1 | 83.3% | 79.7% | 39.6% | 63.4% | Not yet published |
| ||||||||||||
| GPT-5.6 Sol | 37.9% | 57.1% | 89.1% | 93.5% | 49.5% | 60.1% | 62.7%Run by OSWorld teamOSWorld 2.0 | 84% | 83.4% | 69.7%Run by Epoch AISimpleQA Verified | Not yet published | 72.7%Run by Artificial AnalysisIFBench |
| ||||||||||||
| GPT-5.6 Terra | 22.7% | 55% | 86% | 93.3% | 42.9% | 59.6% | Not yet published | 83% | 80.7% | 42.3% | Not yet published | 71.2%Run by Artificial AnalysisIFBench |
| ||||||||||||
| GPT-5.6 Luna | 11.6% | 53.6% | 82.1% | 91.6% | 39.5% | 50.2% | Not yet published | 83.7% | 78.6% | 41%Run by Epoch AISimpleQA Verified | Not yet published | Not yet published |
| ||||||||||||
| GPT-5.5 | 14.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 55.8% | 85.3% | 93.5%Run by Artificial Analysis | 45.8% | 47.3% | 49.5%Run by OSWorld teamOSWorld 2.0 | 84.3% | 79.9% | 63%Run by Epoch AISimpleQA Verified | Not yet published | 75.9%Run by Artificial AnalysisIFBench |
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| GPT-5.4 | Not yet published | Not yet published | 78.6% | 93.3% | 43.7% | Not yet published | Not yet published | 82% | 78.4% | Not yet published | Not yet published | 73.9%Run by Artificial AnalysisIFBench |
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| gpt-oss-120b | 14.2%Run by Terminal-Bench (via Epoch AI)Terminal-Bench 2.0 | 34% | 88.9%Run by Epoch AIOTIS Mock AIME 2024-2025 | 75.8% | 19.6% | 0.2% | Not yet published | 52% | Not yet published | 16.8%Reported by OpenAISimpleQA | 36.3% | 45.3% |
| ||||||||||||
| GPT-6 Sol | 44.4% | 57.6% | 89.8% | 94.3% | 47.9% | 61.6% | 64.4%Reported by OpenAIOSWorld 2.0 | 83.7% | 82.9% | 54.5% | 64% | Not yet published |
| ||||||||||||
| GPT-5.3-Codex | Not yet published | Not yet published | Not yet published | 91.5%Run by Artificial Analysis | 42.5% | Not yet published | Not yet published | 83.3% | 78.5% | Not yet published | Not yet published | 75.4%Run by Artificial AnalysisIFBench |
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| Claude Haiku 5.5 | 36.4% | 55% | 75.1% | 89.6% | 44.4% | 35.4% | 72.4%Reported by AnthropicOSWorld 2.1 | 82.7% | Not yet published | 34.7% | 78.8% | 67.7% |
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| Claude Sonnet 5.5 | 64.1% | 61% | 88.8% | 95.6% | 55% | 71.8% | 80.1%Reported by Anthropic | 82.7% | Not yet published | 51.5% | 81.6% | Not yet published |
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| Claude Opus 5.5 | 65.2% | 66.9% | 91.2% | 90.6% | 61.4% | 69.5% | 81.8%Reported by Anthropic | 84.7% | 87.7% | 65.5% | 82.8% | Not yet published |
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| Claude Fable 5.1 | 58.1% | 63.1% | 90.2% | 93.4%Run by Vals.ai | 59.1% | 59.4% | 80.7%Reported by Anthropic | 85.3% | 86.3%Run by Moonshot AI | 68.4% | 72.4% | Not yet published |
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| Claude Opus 5 | 53.5% | 56.4% | 85.6% | 93.9% | 54.9% | 56.6% | 77.7% | 79.3% | 84.7% | 60.9% | 73.7% | Not yet published |
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| Claude Sonnet 5 | 10.6% | 54.3% | 65.6% | 80.3% | 41.3% | 36.5% | 57%Reported by Anthropic | 82% | 77.3% | 40.1% | Not yet published | Not yet published |
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| Claude Fable 5 | 41.4% | 61% | 87% | 85.9% | 55.5% | 54.1% | Not yet published | 82.3% | Not yet published | 65.4% | 64.8% | 63.5%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.8 | 23.2% | 54.4% | 80% | 91% | 48.7% | 45.6% | 54.8%Run by OSWorld teamOSWorld 2.0 | 77.7% | Not yet published | 48.8% | 67.4% | 62.2%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.7 | Not yet published | 54.5% | 70.2% | 86.4% | 42.3% | Not yet published | 48.9%Run by OSWorld teamOSWorld 2.0 | 78.7% | 78.8% | 48.9% | 70.2% | 58.6%Run by Artificial AnalysisIFBench |
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| Claude Sonnet 4.6 | 3%Run by Artificial AnalysisTerminal-Bench 4.0 | 50.1% | 71.1%Run by Epoch AIOTIS Mock AIME 2024-2025 | 78.8% | 33.6% | 20.1% | 41.5%Run by OSWorld teamOSWorld 2.0 | 80% | 73.3% | 40.9% | 35.8% | 56.6%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.6 | Not yet published | Not yet published | 66% | 88.4% | 39.9% | Not yet published | Not yet published | 78% | 75.4% | 47% | 59.9% | 37.2% |
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| Claude Opus 4.5 | Not yet published | Not yet published | 34.4% | 86% | 30.1% | Not yet published | Not yet published | 77.3% | 74% | 46.6% | 57.5% | 59% |
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| Claude Haiku 4.5 | Not yet published | 42.2% | 66.7%Run by Epoch AIOTIS Mock AIME 2024-2025 | 71.2% | 10.4% | 3.2% | Not yet published | 74.3% | 58.6% | 18% | 24.7% | 50.5% |
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| Claude Sonnet 4.5 | Not yet published | 45.7% | 23.9% | 82.3% | 17.8% | 14.1% | Not yet published | 72.3% | 68.7% | 32.9% | 31.4% | 55.3% |
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| Gemini 4 Argon | 57.6% | 61.8% | 86% | 96.4% | 57.1% | 77.5% | 69.2%Reported by GoogleOSWorld 2.0 | 79.7% | Not yet published | 48.3% | 87% | 78.7% |
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| Gemini 3.8 Flash | 19.7% | 56.6% | 68.4% | 95.4% | 47.8% | 59.9% | 59%Reported by GoogleOSWorld 2.0 | 81.3% | 85.6% | 50.5% | 86.1% | Not yet published |
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| Gemma 4 31B | Not yet published | 45.5% | Not yet published | 85.7%Run by Artificial AnalysisGPQA Diamond | 23.6% | 4.9% | Not yet published | 69.7% | 73.4% | 10.4%Run by Epoch AISimpleQA Verified | 82.3% | 75.6%Run by Artificial AnalysisIFBench |
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| Gemini 3.1 Pro Preview | 2.5% | 58.7% | 59.6% | 94.4% | 47% | 35.4% | Not yet published | 82% | 82.4% | 54.9% | 59.9% | 71.4% |
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| Gemini 3.6 Flash | 7.1%Run by Artificial AnalysisTerminal-Bench 4.0 | 53.4% | 58.9% | 94.1% | 40.8% | 53% | 83%Reported by GoogleOSWorld-Verified | 80% | 83.2% | 66.2%Run by Epoch AISimpleQA Verified | 87.2% | Not yet published |
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| DeepSeek V4.1 Flash | 31.8% | 55.9% | 71.2% | 93.2% | 43.3% | 66.6% | 69.3%Run by Moonshot AIOSWorld 2.1 | 82.7% | 80.6% | 39.6% | Not yet published | 74.9% |
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| DeepSeek V4 Pro | 14.1% | 51% | 64.6% | 91.7% | 41% | 56.7% | Not yet published | 80.3% | Not yet published | 45.2% | 72% | Not yet published |
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| Kimi K3.1 Pro | 63.6% | 60.8% | Not yet published | 94.2%Reported by Moonshot AI | 52.5% | 73.3% | 79.6%Reported by Moonshot AIOSWorld 2.1 | 86.3% | 83.9% | 48.9% | Not yet published | Not yet published |
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| Kimi K3 | 17.2% | 59.5% | 72.2% | 93.1% | 46.9% | 58.3% | Not yet published | 88.7% | 80.5% | 50.6%Run by Epoch AISimpleQA Verified | 65.9% | Not yet published |
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| Kimi K2.7 Code | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 47.8% | 54% | 87.9% | 35% | 24.5% | Not yet published | 79.3% | Not yet published | 36.5%Run by Epoch AISimpleQA Verified | Not yet published | 63.1%Run by Artificial AnalysisIFBench |
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| Mistral Large 4 | 24.7%Run by Artificial AnalysisTerminal-Bench 4.0 | Not yet published | Not yet published | Not yet published | Not yet published | 57.8% | Not yet published | Not yet published | Not yet published | 26% | Not yet published | Not yet published |
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| Mistral Medium 3.5 | 0%Run by Artificial AnalysisTerminal-Bench 4.0 | 40.2% | Not yet published | 74.8%Run by Artificial AnalysisGPQA Diamond | 13.8% | 6.3% | Not yet published | 69.3% | 64.9% | 23% | 70.5% | 68.8%Run by Artificial AnalysisIFBench |
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| Grok 4.7 | 28.8% | 57.4% | 53% | 92.7% | 43.1% | 65.6% | Not yet published | 76.7% | Not yet published | 42.7% | 64.1% | Not yet published |
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| Grok 4.6 | 17.2% | 56.5% | 66% | 93.2% | 42.9% | 66.7% | Not yet published | 80.3% | Not yet published | 48.9%Run by Epoch AISimpleQA Verified | 83.6% | Not yet published |
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| Grok 4.5 | 8.6% | 55% | 57.2% | 93.4% | 42.7% | 57.9% | Not yet published | 79.3% | 80.4% | 48.3%Run by Epoch AISimpleQA Verified | 93.1% | Not yet published |
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| MiniMax M3.1 Flash | 25.3% | 53.4% | Not yet published | Not yet published | 48% | 72.5% | 61.7%Reported by MiniMaxOSWorld 2.0 | 79.7% | 79.1% | 45.1% | Not yet published | Not yet published |
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| Mercury 3 | 3% | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published |
| GLM-5.3-Flash | 37.4% | 51.6% | 55.8% | 90.2% | 39.9% | 60.4% | 59.1%Reported by Z.aiOSWorld 2.0 | 80% | 86%Run by Vals.aiMMMU-Pro | 28.2% | 65.4% | Not yet published |
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| GLM-5.3 | 38.9% | 59% | 68.8% | 90.9% | 42.3% | 62.2% | Not yet published | 79.7% | Not yet published | 32.3% | 71.5% | Not yet published |
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| GLM-5.2 | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 51.2% | 59.2% | Not yet published | 41.1% | 28.4% | Not yet published | 78.3% | Not yet published | 34.2%Run by Epoch AISimpleQA Verified | Not yet published | 73.3%Run by Artificial AnalysisIFBench |
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| Muse Spark Open | 6.6% | 58.4% | 69.8% | 88.6% | 43.9% | 49.7% | 80.4%Reported by MetaOSWorld-Verified | 78.3% | 80.9% | 42% | Not yet published | 74.2% |
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| Muse Wonder | 49.5% | 60.3% | 82.1% | Not yet published | 50.1% | 68.1% | 72.6%Reported by Meta | 80.7% | Not yet published | 38% | 42.7% | Not yet published |
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| Muse Spark 1.3 | 10.6% | 58.8% | 74% | 93.5%Run by Artificial AnalysisGPQA Diamond | 48.7% | 57.9% | 69.6% | 83% | 82% | 38% | 25.8% | Not yet published |
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| Llama 4 Scout | Not yet published | 21.3% | 7.8%Run by Epoch AIOTIS Mock AIME 2024-2025 | 51.8% | 3.8% | 0.2% | Not yet published | 27.7% | 52.9% | Not yet published | 70.1% | 39.5%Run by Artificial AnalysisIFBench |
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| Llama 4 Maverick | Not yet published | 31.7% | 20.6%Run by Epoch AIOTIS Mock AIME 2024-2025 | 67% | 4.9% | 0.2% | Not yet published | 50% | 62.1% | Not yet published | 58.3% | 43%Run by Artificial AnalysisIFBench |
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| Qwen3.8 27B | 5.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 46.6% | Not yet published | 90.5%Run by Artificial AnalysisGPQA Diamond | 33.9% | 48.2% | 84.3%Reported by AlibabaOSWorld-Verified | 82% | 76.3% | 17.3% | Not yet published | 79.5%Reported by AlibabaIFBench |
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| Qwen3.8 Max | 38.9% | 52.1% | 65.6% | 92.3% | 43.1% | 56.2% | Not yet published | 80.3% | 82.8% | 29.5% | 65.3% | Not yet published |
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| MiMo-V2.6-Pro | 31.3% | 60.9% | Not yet published | Not yet published | 49.4% | 58.6% | 82%Reported by XiaomiOSWorld-Verified | 86.3% | Not yet published | 34.8% | 66.5% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Flash | 24.2% | 51.3% | Not yet published | Not yet published | 35.1% | 64.1% | 80.8%Reported by XiaomiOSWorld-Verified | 74.3% | 73.1% | 27.2% | 66.9% | Not yet published |
| ||||||||||||
| Ling 3.1 Flash | 32.8%Run by Artificial AnalysisTerminal-Bench 4.0 | 56.8% | Not yet published | Not yet published | 43.5% | 67.5% | Not yet published | 82.3% | Not yet published | 26.5% | Not yet published | Not yet published |
| ||||||||||||
| Step 5 Preview | 31.8% | 58.9% | Not yet published | 93.5%Reported by StepFunGPQA Diamond | 46.5% | 51% | Not yet published | 88.3% | 76.4% | 36.4% | 59.7% | Not yet published |
| ||||||||||||
Agentic codingTerminal-Bench 4.0
- Claude Opus 5.565.2%
- Claude Sonnet 5.564.1%
- Kimi K3.1 Pro63.6%
- GPT-6 Astra59.6%
- Claude Fable 5.158.1%
- Gemini 4 Argon57.6%
- GPT-6.1 Sol55.1%
- Claude Opus 553.5%
- GPT-6.1 Terra49.5%
- Muse Wonder49.5%
- GPT-6 Sol44.4%
- Claude Fable 541.4%
- GLM-5.338.9%
- Qwen3.8 Max38.9%
- GPT-5.6 Sol37.9%
- GLM-5.3-Flash37.4%
- Claude Haiku 5.536.4%
- DeepSeek V4.1 Flash31.8%
- Step 5 Preview31.8%
- MiMo-V2.6-Pro31.3%
- Grok 4.728.8%
- MiniMax M3.1 Flash25.3%
- MiMo-V2.6-Flash24.2%
- Claude Opus 4.823.2%
- GPT-5.6 Terra22.7%
- Gemini 3.8 Flash19.7%
- Kimi K317.2%
- Grok 4.617.2%
- DeepSeek V4 Pro14.1%
- GPT-6 Luna13.6%
- GPT-5.6 Luna11.6%
- Claude Sonnet 510.6%
- Muse Spark 1.310.6%
- Grok 4.58.6%
- Muse Spark Open6.6%
- Mercury 33%
- Gemini 3.1 Pro Preview2.5%
- Ling 3.1 Flash32.8%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Large 424.7%Artificial Analysis's run, Terminal-Bench 4.0
- GPT-5.514.6%Artificial Analysis's run, Terminal-Bench 4.0
- gpt-oss-120b14.2%Terminal-Bench's run, Terminal-Bench 2.0
- Gemini 3.6 Flash7.1%Artificial Analysis's run, Terminal-Bench 4.0
- Qwen3.8 27B5.6%Artificial Analysis's run, Terminal-Bench 4.0
- Claude Sonnet 4.63%Artificial Analysis's run, Terminal-Bench 4.0
- Kimi K2.7 Code1%Artificial Analysis's run, Terminal-Bench 4.0
- GLM-5.21%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Medium 3.50%Artificial Analysis's run, Terminal-Bench 4.0
The other models in the grid have no result on Terminal-Bench 4.0 yet.
CodeSciCode
- Claude Opus 5.566.9%
- Claude Fable 5.163.1%
- Gemini 4 Argon61.8%
- Claude Sonnet 5.561%
- Claude Fable 561%
- MiMo-V2.6-Pro60.9%
- Kimi K3.1 Pro60.8%
- Muse Wonder60.3%
- Kimi K359.5%
- GLM-5.359%
- Step 5 Preview58.9%
- Muse Spark 1.358.8%
- Gemini 3.1 Pro Preview58.7%
- Muse Spark Open58.4%
- GPT-6 Sol57.6%
- Grok 4.757.4%
- GPT-5.6 Sol57.1%
- Ling 3.1 Flash56.8%
- Gemini 3.8 Flash56.6%
- GPT-6 Astra56.5%
- Grok 4.656.5%
- Claude Opus 556.4%
- DeepSeek V4.1 Flash55.9%
- GPT-5.555.8%
- GPT-6.1 Terra55.1%
- GPT-5.6 Terra55%
- Claude Haiku 5.555%
- Grok 4.555%
- GPT-6 Luna54.6%
- Claude Opus 4.754.5%
- Claude Opus 4.854.4%
- Claude Sonnet 554.3%
- GPT-6.1 Sol54.2%
- GPT-5.6 Luna53.6%
- Gemini 3.6 Flash53.4%
- MiniMax M3.1 Flash53.4%
- Qwen3.8 Max52.1%
- GLM-5.3-Flash51.6%
- MiMo-V2.6-Flash51.3%
- GLM-5.251.2%
- DeepSeek V4 Pro51%
- Claude Sonnet 4.650.1%
- Kimi K2.7 Code47.8%
- Qwen3.8 27B46.6%
- Claude Sonnet 4.545.7%
- Gemma 4 31B45.5%
- Claude Haiku 4.542.2%
- Mistral Medium 3.540.2%
- gpt-oss-120b34%
- Llama 4 Maverick31.7%
- Llama 4 Scout21.3%
The other models in the grid have no result on SciCode yet.
MathFrontierMath Tiers 1-3
- GPT-6 Astra93.7%
- GPT-6.1 Sol93.7%
- Claude Opus 5.591.2%
- GPT-6.1 Terra90.9%
- Claude Fable 5.190.2%
- GPT-6 Sol89.8%
- GPT-5.6 Sol89.1%
- Claude Sonnet 5.588.8%
- Claude Fable 587%
- GPT-5.6 Terra86%
- Gemini 4 Argon86%
- Claude Opus 585.6%
- GPT-5.585.3%
- GPT-5.6 Luna82.1%
- Muse Wonder82.1%
- Claude Opus 4.880%
- GPT-6 Luna78.9%
- GPT-5.478.6%
- Claude Haiku 5.575.1%
- Muse Spark 1.374%
- Kimi K372.2%
- DeepSeek V4.1 Flash71.2%
- Claude Opus 4.770.2%
- Muse Spark Open69.8%
- GLM-5.368.8%
- Gemini 3.8 Flash68.4%
- Claude Opus 4.666%
- Grok 4.666%
- Claude Sonnet 565.6%
- Qwen3.8 Max65.6%
- DeepSeek V4 Pro64.6%
- Gemini 3.1 Pro Preview59.6%
- GLM-5.259.2%
- Gemini 3.6 Flash58.9%
- Grok 4.557.2%
- GLM-5.3-Flash55.8%
- Kimi K2.7 Code54%
- Grok 4.753%
- Claude Opus 4.534.4%
- Claude Sonnet 4.523.9%
- gpt-oss-120b88.9%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Sonnet 4.671.1%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Haiku 4.566.7%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Maverick20.6%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Scout7.8%Epoch AI's run, OTIS Mock AIME 2024-2025
The other models in the grid have no result on FrontierMath Tiers 1-3 yet.
ScienceGPQA Diamond
- Gemini 4 Argon96.4%
- GPT-6 Astra95.8%
- Claude Sonnet 5.595.6%
- GPT-6.1 Sol95.4%
- Gemini 3.8 Flash95.4%
- Gemini 3.1 Pro Preview94.4%
- GPT-6.1 Terra94.3%
- GPT-6 Sol94.3%
- Gemini 3.6 Flash94.1%
- Claude Opus 593.9%
- GPT-5.6 Sol93.5%
- Grok 4.593.4%
- GPT-5.6 Terra93.3%
- GPT-5.493.3%
- DeepSeek V4.1 Flash93.2%
- Grok 4.693.2%
- Kimi K393.1%
- Grok 4.792.7%
- Qwen3.8 Max92.3%
- DeepSeek V4 Pro91.7%
- GPT-5.6 Luna91.6%
- Claude Opus 4.891%
- GLM-5.390.9%
- Claude Opus 5.590.6%
- GPT-6 Luna90.5%
- GLM-5.3-Flash90.2%
- Claude Haiku 5.589.6%
- Muse Spark Open88.6%
- Claude Opus 4.688.4%
- Kimi K2.7 Code87.9%
- Claude Opus 4.786.4%
- Claude Opus 4.586%
- Claude Fable 585.9%
- Claude Sonnet 4.582.3%
- Claude Sonnet 580.3%
- Claude Sonnet 4.678.8%
- gpt-oss-120b75.8%
- Claude Haiku 4.571.2%
- Llama 4 Maverick67%
- Llama 4 Scout51.8%
- Kimi K3.1 Pro94.2%Moonshot AI's own figure
- GPT-5.593.5%Artificial Analysis's run
- Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
- Step 5 Preview93.5%StepFun's own figure, GPQA Diamond
- Claude Fable 5.193.4%Vals.ai's run
- GPT-5.3-Codex91.5%Artificial Analysis's run
- Qwen3.8 27B90.5%Artificial Analysis's run, GPQA Diamond
- Gemma 4 31B85.7%Artificial Analysis's run, GPQA Diamond
- Mistral Medium 3.574.8%Artificial Analysis's run, GPQA Diamond
The other models in the grid have no result on GPQA Diamond yet.
Hard reasoningHumanity's Last Exam
- Claude Opus 5.561.4%
- Claude Fable 5.159.1%
- Gemini 4 Argon57.1%
- Claude Fable 555.5%
- Claude Sonnet 5.555%
- Claude Opus 554.9%
- GPT-6 Astra54.7%
- GPT-6.1 Sol52.9%
- Kimi K3.1 Pro52.5%
- Muse Wonder50.1%
- GPT-5.6 Sol49.5%
- MiMo-V2.6-Pro49.4%
- Claude Opus 4.848.7%
- Muse Spark 1.348.7%
- MiniMax M3.1 Flash48%
- GPT-6 Sol47.9%
- Gemini 3.8 Flash47.8%
- Gemini 3.1 Pro Preview47%
- Kimi K346.9%
- Step 5 Preview46.5%
- GPT-6.1 Terra46.2%
- GPT-5.545.8%
- Claude Haiku 5.544.4%
- Muse Spark Open43.9%
- GPT-5.443.7%
- Ling 3.1 Flash43.5%
- DeepSeek V4.1 Flash43.3%
- Grok 4.743.1%
- Qwen3.8 Max43.1%
- GPT-5.6 Terra42.9%
- Grok 4.642.9%
- Grok 4.542.7%
- GPT-5.3-Codex42.5%
- Claude Opus 4.742.3%
- GLM-5.342.3%
- Claude Sonnet 541.3%
- GLM-5.241.1%
- DeepSeek V4 Pro41%
- Gemini 3.6 Flash40.8%
- Claude Opus 4.639.9%
- GLM-5.3-Flash39.9%
- GPT-5.6 Luna39.5%
- GPT-6 Luna38.5%
- MiMo-V2.6-Flash35.1%
- Kimi K2.7 Code35%
- Qwen3.8 27B33.9%
- Claude Sonnet 4.633.6%
- Claude Opus 4.530.1%
- Gemma 4 31B23.6%
- gpt-oss-120b19.6%
- Claude Sonnet 4.517.8%
- Mistral Medium 3.513.8%
- Claude Haiku 4.510.4%
- Llama 4 Maverick4.9%
- Llama 4 Scout3.8%
The other models in the grid have no result on Humanity's Last Exam yet.
Tool useAutomationBench-AA
- Gemini 4 Argon77.5%
- Kimi K3.1 Pro73.3%
- MiniMax M3.1 Flash72.5%
- Claude Sonnet 5.571.8%
- Claude Opus 5.569.5%
- GPT-6 Astra68.5%
- Muse Wonder68.1%
- Ling 3.1 Flash67.5%
- Grok 4.666.7%
- DeepSeek V4.1 Flash66.6%
- Grok 4.765.6%
- GPT-6.1 Sol64.9%
- MiMo-V2.6-Flash64.1%
- GLM-5.362.2%
- GPT-6 Sol61.6%
- GLM-5.3-Flash60.4%
- GPT-6.1 Terra60.2%
- GPT-5.6 Sol60.1%
- Gemini 3.8 Flash59.9%
- GPT-5.6 Terra59.6%
- Claude Fable 5.159.4%
- MiMo-V2.6-Pro58.6%
- Kimi K358.3%
- Grok 4.557.9%
- Muse Spark 1.357.9%
- Mistral Large 457.8%
- DeepSeek V4 Pro56.7%
- Claude Opus 556.6%
- Qwen3.8 Max56.2%
- Claude Fable 554.1%
- GPT-6 Luna53.2%
- Gemini 3.6 Flash53%
- Step 5 Preview51%
- GPT-5.6 Luna50.2%
- Muse Spark Open49.7%
- Qwen3.8 27B48.2%
- GPT-5.547.3%
- Claude Opus 4.845.6%
- Claude Sonnet 536.5%
- Claude Haiku 5.535.4%
- Gemini 3.1 Pro Preview35.4%
- GLM-5.228.4%
- Kimi K2.7 Code24.5%
- Claude Sonnet 4.620.1%
- Claude Sonnet 4.514.1%
- Mistral Medium 3.56.3%
- Gemma 4 31B4.9%
- Claude Haiku 4.53.2%
- gpt-oss-120b0.2%
- Llama 4 Scout0.2%
- Llama 4 Maverick0.2%
The other models in the grid have no result on AutomationBench-AA yet.
Computer useOSWorld 2.1
- Claude Opus 577.7%
- Muse Spark 1.369.6%
- Qwen3.8 27B84.3%Alibaba's own figure, OSWorld-Verified
- Gemini 3.6 Flash83%Google's own figure, OSWorld-Verified
- MiMo-V2.6-Pro82%Xiaomi's own figure, OSWorld-Verified
- Claude Opus 5.581.8%Anthropic's own figure
- MiMo-V2.6-Flash80.8%Xiaomi's own figure, OSWorld-Verified
- Claude Fable 5.180.7%Anthropic's own figure
- Muse Spark Open80.4%Meta's own figure, OSWorld-Verified
- Claude Sonnet 5.580.1%Anthropic's own figure
- Kimi K3.1 Pro79.6%Moonshot AI's own figure, OSWorld 2.1
- GPT-6.1 Sol78%OpenAI's own figure, OSWorld 2.1
- GPT-6 Astra75.8%Meta's run
- GPT-6.1 Terra74.2%OpenAI's own figure, OSWorld 2.1
- Muse Wonder72.6%Meta's own figure
- Claude Haiku 5.572.4%Anthropic's own figure, OSWorld 2.1
- DeepSeek V4.1 Flash69.3%Moonshot AI's run, OSWorld 2.1
- Gemini 4 Argon69.2%Google's own figure, OSWorld 2.0
- GPT-6 Sol64.4%OpenAI's own figure, OSWorld 2.0
- GPT-5.6 Sol62.7%OSWorld team's run, OSWorld 2.0
- MiniMax M3.1 Flash61.7%MiniMax's own figure, OSWorld 2.0
- GLM-5.3-Flash59.1%Z.ai's own figure, OSWorld 2.0
- Gemini 3.8 Flash59%Google's own figure, OSWorld 2.0
- Claude Sonnet 557%Anthropic's own figure
- Claude Opus 4.854.8%OSWorld team's run, OSWorld 2.0
- GPT-5.549.5%OSWorld team's run, OSWorld 2.0
- GPT-6 Luna48.9%Anthropic's run, OSWorld 2.1
- Claude Opus 4.748.9%OSWorld team's run, OSWorld 2.0
- Claude Sonnet 4.641.5%OSWorld team's run, OSWorld 2.0
The other models in the grid have no result on OSWorld 2.1 yet.
Long contextAA-LCR v1.1
- Kimi K388.7%
- Step 5 Preview88.3%
- Kimi K3.1 Pro86.3%
- MiMo-V2.6-Pro86.3%
- Claude Fable 5.185.3%
- Claude Opus 5.584.7%
- GPT-5.584.3%
- GPT-5.6 Sol84%
- GPT-5.6 Luna83.7%
- GPT-6 Sol83.7%
- GPT-6 Luna83.3%
- GPT-5.3-Codex83.3%
- GPT-6.1 Sol83%
- GPT-5.6 Terra83%
- Muse Spark 1.383%
- GPT-6.1 Terra82.7%
- Claude Haiku 5.582.7%
- Claude Sonnet 5.582.7%
- DeepSeek V4.1 Flash82.7%
- Claude Fable 582.3%
- Ling 3.1 Flash82.3%
- GPT-5.482%
- Claude Sonnet 582%
- Gemini 3.1 Pro Preview82%
- Qwen3.8 27B82%
- Gemini 3.8 Flash81.3%
- GPT-6 Astra80.7%
- Muse Wonder80.7%
- DeepSeek V4 Pro80.3%
- Grok 4.680.3%
- Qwen3.8 Max80.3%
- Claude Sonnet 4.680%
- Gemini 3.6 Flash80%
- GLM-5.3-Flash80%
- Gemini 4 Argon79.7%
- MiniMax M3.1 Flash79.7%
- GLM-5.379.7%
- Claude Opus 579.3%
- Kimi K2.7 Code79.3%
- Grok 4.579.3%
- Claude Opus 4.778.7%
- GLM-5.278.3%
- Muse Spark Open78.3%
- Claude Opus 4.678%
- Claude Opus 4.877.7%
- Claude Opus 4.577.3%
- Grok 4.776.7%
- Claude Haiku 4.574.3%
- MiMo-V2.6-Flash74.3%
- Claude Sonnet 4.572.3%
- Gemma 4 31B69.7%
- Mistral Medium 3.569.3%
- gpt-oss-120b52%
- Llama 4 Maverick50%
- Llama 4 Scout27.7%
The other models in the grid have no result on AA-LCR v1.1 yet.
MultimodalMMMU-Pro
- Claude Opus 5.587.7%
- GPT-6 Astra86.9%
- GPT-6.1 Sol86%
- Gemini 3.8 Flash85.6%
- GPT-6.1 Terra84.7%
- Claude Opus 584.7%
- Kimi K3.1 Pro83.9%
- GPT-5.6 Sol83.4%
- Gemini 3.6 Flash83.2%
- GPT-6 Sol82.9%
- Qwen3.8 Max82.8%
- Gemini 3.1 Pro Preview82.4%
- Muse Spark 1.382%
- Muse Spark Open80.9%
- GPT-5.6 Terra80.7%
- DeepSeek V4.1 Flash80.6%
- Kimi K380.5%
- Grok 4.580.4%
- GPT-5.579.9%
- GPT-6 Luna79.7%
- MiniMax M3.1 Flash79.1%
- Claude Opus 4.778.8%
- GPT-5.6 Luna78.6%
- GPT-5.3-Codex78.5%
- GPT-5.478.4%
- Claude Sonnet 577.3%
- Step 5 Preview76.4%
- Qwen3.8 27B76.3%
- Claude Opus 4.675.4%
- Claude Opus 4.574%
- Gemma 4 31B73.4%
- Claude Sonnet 4.673.3%
- MiMo-V2.6-Flash73.1%
- Claude Sonnet 4.568.7%
- Mistral Medium 3.564.9%
- Llama 4 Maverick62.1%
- Claude Haiku 4.558.6%
- Llama 4 Scout52.9%
- Claude Fable 5.186.3%Moonshot AI's run
- GLM-5.3-Flash86%Vals.ai's run, MMMU-Pro
The other models in the grid have no result on MMMU-Pro yet.
FactualityAA-Omniscience Accuracy
- Claude Fable 5.168.4%
- Claude Opus 5.565.5%
- Claude Fable 565.4%
- GPT-6.1 Sol61.8%
- GPT-6 Astra61.6%
- Claude Opus 560.9%
- Gemini 3.1 Pro Preview54.9%
- GPT-6 Sol54.5%
- Claude Sonnet 5.551.5%
- Gemini 3.8 Flash50.5%
- Claude Opus 4.748.9%
- Kimi K3.1 Pro48.9%
- Claude Opus 4.848.8%
- Gemini 4 Argon48.3%
- GPT-6.1 Terra47.6%
- Claude Opus 4.647%
- Claude Opus 4.546.6%
- DeepSeek V4 Pro45.2%
- MiniMax M3.1 Flash45.1%
- Grok 4.742.7%
- GPT-5.6 Terra42.3%
- Muse Spark Open42%
- Claude Sonnet 4.640.9%
- Claude Sonnet 540.1%
- GPT-6 Luna39.6%
- DeepSeek V4.1 Flash39.6%
- Muse Wonder38%
- Muse Spark 1.338%
- Step 5 Preview36.4%
- MiMo-V2.6-Pro34.8%
- Claude Haiku 5.534.7%
- Claude Sonnet 4.532.9%
- GLM-5.332.3%
- Qwen3.8 Max29.5%
- GLM-5.3-Flash28.2%
- MiMo-V2.6-Flash27.2%
- Ling 3.1 Flash26.5%
- Mistral Large 426%
- Mistral Medium 3.523%
- Claude Haiku 4.518%
- Qwen3.8 27B17.3%
- GPT-5.6 Sol69.7%Epoch AI's run, SimpleQA Verified
- Gemini 3.6 Flash66.2%Epoch AI's run, SimpleQA Verified
- GPT-5.563%Epoch AI's run, SimpleQA Verified
- Kimi K350.6%Epoch AI's run, SimpleQA Verified
- Grok 4.648.9%Epoch AI's run, SimpleQA Verified
- Grok 4.548.3%Epoch AI's run, SimpleQA Verified
- GPT-5.6 Luna41%Epoch AI's run, SimpleQA Verified
- Kimi K2.7 Code36.5%Epoch AI's run, SimpleQA Verified
- GLM-5.234.2%Epoch AI's run, SimpleQA Verified
- gpt-oss-120b16.8%OpenAI's own figure, SimpleQA
- Gemma 4 31B10.4%Epoch AI's run, SimpleQA Verified
The other models in the grid have no result on AA-Omniscience Accuracy yet.
Answers in fullSpeechMap
- Grok 4.593.1%
- Gemini 3.6 Flash87.2%
- Gemini 4 Argon87%
- Gemini 3.8 Flash86.1%
- Grok 4.683.6%
- Claude Opus 5.582.8%
- Gemma 4 31B82.3%
- Claude Sonnet 5.581.6%
- Claude Haiku 5.578.8%
- Claude Opus 573.7%
- Claude Fable 5.172.4%
- DeepSeek V4 Pro72%
- GLM-5.371.5%
- Mistral Medium 3.570.5%
- Claude Opus 4.770.2%
- Llama 4 Scout70.1%
- GPT-6.1 Sol69.5%
- GPT-6 Astra68.2%
- Claude Opus 4.867.4%
- MiMo-V2.6-Flash66.9%
- MiMo-V2.6-Pro66.5%
- Kimi K365.9%
- GLM-5.3-Flash65.4%
- Qwen3.8 Max65.3%
- Claude Fable 564.8%
- Grok 4.764.1%
- GPT-6 Sol64%
- GPT-6 Luna63.4%
- Claude Opus 4.659.9%
- Gemini 3.1 Pro Preview59.9%
- Step 5 Preview59.7%
- Llama 4 Maverick58.3%
- Claude Opus 4.557.5%
- Muse Wonder42.7%
- gpt-oss-120b36.3%
- Claude Sonnet 4.635.8%
- Claude Sonnet 4.531.4%
- Muse Spark 1.325.8%
- Claude Haiku 4.524.7%
The other models in the grid have no result on SpeechMap yet.
Instruction followingMultiChallenge
- GPT-6.1 Sol82%
- Gemini 4 Argon78.7%
- DeepSeek V4.1 Flash74.9%
- GPT-6.1 Terra74.2%
- Muse Spark Open74.2%
- Gemini 3.1 Pro Preview71.4%
- Claude Haiku 5.567.7%
- Claude Opus 4.559%
- Claude Sonnet 4.555.3%
- Claude Haiku 4.550.5%
- gpt-oss-120b45.3%
- Claude Opus 4.637.2%
- Qwen3.8 27B79.5%Alibaba's own figure, IFBench
- GPT-5.575.9%Artificial Analysis's run, IFBench
- Gemma 4 31B75.6%Artificial Analysis's run, IFBench
- GPT-5.3-Codex75.4%Artificial Analysis's run, IFBench
- GPT-5.473.9%Artificial Analysis's run, IFBench
- GLM-5.273.3%Artificial Analysis's run, IFBench
- GPT-5.6 Sol72.7%Artificial Analysis's run, IFBench
- GPT-5.6 Terra71.2%Artificial Analysis's run, IFBench
- Mistral Medium 3.568.8%Artificial Analysis's run, IFBench
- Claude Fable 563.5%Artificial Analysis's run, IFBench
- Kimi K2.7 Code63.1%Artificial Analysis's run, IFBench
- Claude Opus 4.862.2%Artificial Analysis's run, IFBench
- Claude Opus 4.758.6%Artificial Analysis's run, IFBench
- Claude Sonnet 4.656.6%Artificial Analysis's run, IFBench
- Llama 4 Maverick43%Artificial Analysis's run, IFBench
- Llama 4 Scout39.5%Artificial Analysis's run, IFBench
The other models in the grid have no result on MultiChallenge yet.
Every measure on record
Cost, speed, reliability, knowledge-work and domain results for GPT-6 Astra beyond the twelve chart axes, each with the run it comes from and its publisher. These stay separate measures; none is folded into the chart.
| Measure | GPT-6 Astra | Run | Source | Read |
|---|---|---|---|---|
| Specs and access | ||||
| Context windowThe most tokens one request can hold, as the maker states it. Size alone says nothing about how well the model uses a long input; the Long context axis measures that. | 1.05M | OpenAI | Oct 28, 2026 | |
| Max outputThe most tokens the model writes in one response. | 128K | OpenAI | Oct 28, 2026 | |
| ReadsThe kinds of input the model accepts. | Text, Images | Artificial Analysis | Oct 26, 2026 | |
| LicenceThe terms the weights or the service are offered under. | OpenAI Services Agreement | OpenAI | Nov 1, 2026 | |
| Open weightsWhether the maker publishes the weights for anyone to run. | No | Artificial Analysis | Oct 26, 2026 | |
| Routes offering itOf the 19 clouds, gateways and coding products GILD tracks, how many offer the release today, preview included. | 10 of 19 | GILD route matrix | Oct 28, 2026 | |
| Cost | ||||
| Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded. | 10,514 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task. | $0.98 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task. | $0.7 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task. | $1.90 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task. | $1.36 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task. | $0.83 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost per taskLower is better. What one Intelligence Index task cost AA at list price, input, cache, output and reasoning tokens together. | $3.26 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Cost to run the indexLower is better. What the whole Intelligence Index run cost AA at list price. The runs cost from tens of dollars to about $13,000, so the axis is log from $10 to $100,000. | $5,324 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Output tokens per taskLower is better. Tokens the model wrote per Intelligence Index task, reasoning included: how verbose it is. | 27,206 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 16,691 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Speed | ||||
| End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt. | 195 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 389 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Time to first answer token, 100K promptLower is better. Median seconds to the first answer token with a 100,000-token prompt. | 189 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Time to first answer tokenLower is better. Seconds until the first answer token, after any reasoning, on AA's API runs. | 381 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long. | 74 tokens/s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Output speedMedian output tokens per second on AA's API runs, with the 5th and 95th percentile when AA prints them. | 66 tokens/s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Time per taskLower is better. Wall-clock seconds per Intelligence Index task. Runs take from about 15 s to about 33 min, so the axis is log from 1 s to 10,000 s. | 399 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Time to first token, 100K promptLower is better. Median seconds to the first chunk when the prompt is about 100,000 tokens long: long-input latency, separate from window size. | 189 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Time to first tokenLower is better. Median seconds to the first streamed chunk on AA's API runs, with the 5th and 95th percentile when AA prints them. Reasoning models spend this time thinking. | 381 s | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Reliability | ||||
| Hallucination rateLower is better. AA-Omniscience hallucination rate shows how often the model answers wrongly when it does not know and should decline. | 49.8% | Max effort | Artificial Analysis | Oct 28, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 61.6% | Max effort | Artificial Analysis | Oct 28, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 43.4 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| SimpleQA Verified (Epoch)Share of SimpleQA Verified factual questions answered correctly, best scorer, Epoch AI's run. A second factuality source beside AA-Omniscience. | 75.6% | Max effort | Epoch AI | Aug 30, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,568 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows. | 51.3% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it. | 64.7% | Mercor (via Epoch AI) | Oct 26, 2026 | |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 31% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval. | 1,584 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| MLCR (AA run)AA's MLCR overall score for long, multi-document reading. | 41.7% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Vending-Bench 2Vending-Bench 2 final balance of a simulated vending business run by the model, as Epoch AI republishes it. | $15,515 | Andon Labs (via Epoch AI) | Oct 26, 2026 | |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 80.7% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it. | 2,951 | Max effort | Sakana AI (via Epoch AI) | Oct 26, 2026 |
| ARC-AGI-2ARC-AGI-2 score from the ARC Prize maintainers, as Epoch AI republishes it. | 95% | Max effort | ARC Prize Foundation (via Epoch AI) | Oct 26, 2026 |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 74% | Max effort | Epoch AI | Oct 13, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 31.7% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| DeepSWEDeepSWE pass@1, as Epoch AI republishes it. | 73.2% | Max effort | Datacurve (via Epoch AI) | Oct 26, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 97.3% | Extra-high effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| Epoch Capabilities IndexEpoch Capabilities Index: Epoch AI's composite across its benchmark hub, with its confidence interval. | 169 | GPT-6 Astra | Epoch AI | Oct 26, 2026 |
| FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks. | 47.0% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run. | 97.6% | Max effort | Epoch AI | Aug 30, 2026 |
| FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run. | 93.7% | Max effort | Epoch AI | Aug 30, 2026 |
| FrontierSWEFrontierSWE score, as Epoch AI republishes it. | 65.5% | Max effort | FrontierSWE (via Epoch AI) | Oct 26, 2026 |
| GPQA Diamond (AA run)GPQA Diamond accuracy in AA's run. | 96.1% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 95.8% | Max effort | Epoch AI | Aug 30, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 54.7% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 52.7 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents. | 48.6% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| LMCALMCA score, 0 to 100, as Epoch AI republishes it. Its interval is printed only as a half-width, so it is not drawn. | 64.4 | Extra-high effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 86.9% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run. | 84% | Max effort | Epoch AI | Aug 30, 2026 |
| OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run. | 100% | Max effort | Epoch AI | Aug 30, 2026 |
| ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it. | 99% | Vals AI (via Epoch AI) | Oct 26, 2026 | |
| SciCode (AA run)SciCode subproblem accuracy in AA's run. | 56.5% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| tau-Banking (AA run)AA's tau-Banking tool-use score. | 41.4% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness. | 59.1% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness. | 63.3% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| WebDev ArenaWebDev Arena score from human pairwise votes on web builds, with its 95% interval, as Epoch AI republishes it. | 1,800 | Max effort | LMArena (via Epoch AI) | Oct 26, 2026 |
| WeirdML v3, best runWeirdML v3 maximum performance across runs, as Epoch AI republishes it. | 54.0% | Extra-high effort | Håvard Tveit Ihle (via Epoch AI) | Oct 26, 2026 |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 59.8 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 54.7 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 55.2 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points. | 52.7 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 58.5 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 57.3 | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
| Harvey Legal Lab (AA run)AA's run of Harvey's legal task lab. | 8.6% | GPT-6 Astra (Max) | Artificial Analysis | Oct 26, 2026 |
Routes, prices and uptime
Where GPT-6 Astra is offered, what each route charges, and how each endpoint is holding up.
Where it is offered
10 of 19 routes GILD tracks offer GPT-6 Astra today, preview included. Read Oct 28, 2026 from each route's own pages.
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Amazon Bedrock | Available | openai.gpt-6-astra | us./global. profiles on bedrock-runtime (no in-Region); bedrock-mantle us-east-1 and us-west-2; EOL not sooner than Sept 8, 2027; tiers: Standard, Ultrafast (Priority, Flex, Reserved not supported) | Amazon Web Services, Models at a glanceAmazon Web Services, GPT-6 Astra |
| Codex | Available | gpt-6-astra | codex -m gpt-6-astra | OpenAI, Models |
| Databricks | Available | databricks-gpt-6-astra | GPT-6 Astra listed | Databricks, Databricks-hosted inferenceDatabricks, Detailed list of models supported by Databricks Foundation Model APIs |
| The maker's own API | Available | gpt-6-astra | 1,050,000 context / 128,000 output; Fast 2x, Ultrafast 6x, Batch and Flex -50%, regional +10%, >272K input 2x input and 1.5x output | OpenAI, GPT-6 Astra ModelOpenAI, GPT-6.1 Sol ModelOpenAI, GPT-6 Luna Model |
| GitHub Copilot | Available | not statedpicker label GPT-6 Astra | available (GA) | GitHub |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub, GitHub Models |
| Microsoft Foundry | Available | gpt-6-astra | 1,050,000 context (input 922,000, output 128,000) | Microsoft, Foundry Models sold by AzureMicrosoft, Region availability for Foundry Models sold by Azure |
| OpenCode | Available | gpt-6-astra | OpenCode Zen, OpenAI Responses endpoint | Anomaly (OpenCode), ModelsOpenCode (Anomaly) |
| OpenRouter | Available | openai/gpt-6-astra | 1,050,000 / 128,000; batch variant listed | OpenRouter, OpenRouter model list (API)OpenRouter, OpenRouter endpoints for openai/gpt-6-astra-20260903 |
| Snowflake Cortex | Preview | openai-gpt-6-astra | Private preview | Snowflake |
| Windsurf / Devin | Available | gpt-6-astra-highgpt-6-astra-lowgpt-6-astra-maxgpt-6-astra-mediumgpt-6-astra-xhighgpt-6-astra-high-prioritygpt-6-astra-low-prioritygpt-6-astra-medium-prioritygpt-6-astra-max-prioritygpt-6-astra-xhigh-priority | Low to Max thinking, plus Fast (priority) variants | Cognition (Devin, formerly Windsurf), AI ModelsCognition (Devin, formerly Windsurf), 2026 |
Not offered on 3 routes: Antigravity, Cursor and Google Cloud Vertex / Agent Platform (Google managed).
5 routes do not say: Claude Code, Claude on Google Cloud (Anthropic managed), Claude Platform on AWS, Gemini CLI and Grok Build.
What each of these 8 routes' pages say, with sources
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Antigravity | Not offered | Antigravity lists GPT-OSS-120b only among OpenAI models | ||
| Cursor | Not offered | Cursor's OpenAI rows stop at GPT-5.6 Sol, Terra, Luna | Anysphere (Cursor)CursorX (@thegitai) | |
| Google Cloud Vertex / Agent Platform (Google managed) | Not offered | OpenAI section lists gpt-oss only | Google Cloud, Anthropic's Claude on Google Cloud modelsGoogle Cloud, Gemini Enterprise Agent Platform partner models for MaaS | |
| Claude Code | Not stated | Claude Code's model configuration page, read Oct 28 and Oct 29, 2026, does not name this model. It takes a full model name on the Anthropic API, an inference profile ARN on Amazon Bedrock and a deployment name on Microsoft Foundry. | Anthropic | |
| Claude on Google Cloud (Anthropic managed) | Not stated | Region, tier and limits not stated on the route's pages. | ||
| Claude Platform on AWS | Not stated | Region, tier and limits not stated on the route's pages. | ||
| Gemini CLI | Not stated | Region, tier and limits not stated on the route's pages. | ||
| Grok Build | Not stated | Grok Build pages name only grok-4.7 | xAI (SpaceXSI) |
Prices by route
The lowest standard rate is OpenAI API, at $10 / $50 per million input and output tokens. US dollars per million tokens, as each route lists them, one row per route and rate plan, cheapest standard rate first after the maker's own; a blended rate states its mix. OpenRouter's endpoints follow under one heading, each with its monitor's uptime over 1 day and 30 minutes and the context and output it serves.
| Route | Standard, in / out | Cache read | Other rates | Source, or uptime (1 day / 30 min) and limits |
|---|---|---|---|---|
| OpenAI APIMakerLowest | $10 / $50 | OpenAI, Oct 26, 2026 | ||
| Artificial Analysis price record | $10 / $50 | $1 | Blended $20, 3 input : 1 output, no cacheBlended $7.70, 7 cache-hit : 2 input : 1 outputCache write $12.50 | Artificial Analysis, Oct 26, 2026 |
| OpenRouterprompts under 272K tokens | $10 / $50 | $1 | Cache read $2, prompts of 272K tokens or moreCache write $25, 5-minute cache, prompts of 272K tokens or moreCache write $12.50, 5-minute cache, prompts under 272K tokensLong context $20 / $75, prompts of 272K tokens or more | OpenRouter, Oct 28, 2026 |
| Through OpenRouter, 7 provider endpoints. OpenRouter, Oct 28, 2026 | ||||
| Azureprompts under 272K tokens | $10 / $50 | $1 | Cache read $2, prompts of 272K tokens or moreCache write $25, 5-minute cache, prompts of 272K tokens or moreCache write $12.50, 5-minute cache, prompts under 272K tokensLong context $20 / $75, prompts of 272K tokens or more | Up 79.1% / 100%1.05M context, 128K output |
| OpenAIprompts under 272K tokens | $10 / $50 | $1 | Cache read $2, prompts of 272K tokens or moreCache write $25, 5-minute cache, prompts of 272K tokens or moreCache write $12.50, 5-minute cache, prompts under 272K tokensLong context $20 / $75, prompts of 272K tokens or more | Up 100% / 100%1.05M context, 128K output |
| Amazon Bedrock (us-west-2)prompts under 272K tokens | $11 / $55 | $1.10 | Cache read $2.20, prompts of 272K tokens or moreCache write $27.50, 5-minute cache, prompts of 272K tokens or moreCache write $13.75, 5-minute cache, prompts under 272K tokensLong context $22 / $82.50, prompts of 272K tokens or more | 1.05M context, 128K output |
| Azure (us)prompts under 272K tokens | $11 / $55 | $1.10 | Cache read $2.20, prompts of 272K tokens or moreCache write $27.50, 5-minute cache, prompts of 272K tokens or moreCache write $13.75, 5-minute cache, prompts under 272K tokensLong context $22 / $82.50, prompts of 272K tokens or more | Up 96.3%1.05M context, 128K output |
| OpenAI (ultrafast)prompts under 272K tokens | $60 / $300 | $6 | Cache read $12, prompts of 272K tokens or moreCache write $150, 5-minute cache, prompts of 272K tokens or moreCache write $75, 5-minute cache, prompts under 272K tokensLong context $120 / $450, prompts of 272K tokens or more | Up 100%1.05M context, 128K output |
| OpenAI (fast, priority) | Cache read $4, priority tier, prompts of 272K tokens or moreCache read $2, priority tier, prompts under 272K tokensCache write $50, priority tier, 5-minute cache, prompts of 272K tokens or moreCache write $25, priority tier, 5-minute cache, prompts under 272K tokensLong context $40 / $150, priority tier, prompts of 272K tokens or morePriority $20 / $100, priority tier, prompts under 272K tokens | Up 100%1.05M context, 128K output | ||
| OpenAI (flex) | Cache read $1, flex tier, prompts of 272K tokens or moreCache read $0.5, flex tier, prompts under 272K tokensCache write $12.50, flex tier, 5-minute cache, prompts of 272K tokens or moreCache write $6.25, flex tier, 5-minute cache, prompts under 272K tokensFlex $5 / $25, flex tier, prompts under 272K tokensLong context $10 / $37.50, flex tier, prompts of 272K tokens or more | Up 99.5% / 100%1.05M context, 128K output | ||
Uptime and speed by endpoint
Each provider endpoint as its monitor reports it: uptime over the last day and the last 30 minutes, output speed and time to first token, and the limits it serves. A blank is a figure the monitor does not publish for that endpoint.
| Endpoint | Uptime, 1 day | Uptime, 30 min | Output speed | First token | Context / max output | Source |
|---|---|---|---|---|---|---|
| Artificial Analysis: Amazon Bedrock | 91 tokens/s | 263 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: Microsoft Azure | 61 tokens/s | 254 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: OpenAI (Flex) | 98 tokens/s | 260 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: OpenAI | 71 tokens/s | 269 s | Artificial Analysis, Oct 28, 2026 | |||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100.0%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100.0%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100.0%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 | ||||
| Status page: OpenAI API aggregate | 100%, Displayed window: Jul 30, 2026 to Oct 28, 2026; aggregate across tiers, models, and error types where the page states this limitation. | OpenAI, Oct 28, 2026 |
Lineup
OpenAI's 12 releases in 7 families, oldest to newest along each tier, with list price and speed. GPT-6 Astra is lit.
CurrentLegacyThis model
Price is the list price per 1M tokens, input / output. Speed is median output tokens per second. Bars share one scale across the lineup. Read between Oct 26, 2026 and Nov 2, 2026.
GPT Terra
OpenAI's fast, efficient GPT tier for visual reasoning, computer use, and writing.
2 releases
GPT Sol
OpenAI's GPT model tier for demanding everyday and agentic work.
3 releases
GPT Luna
OpenAI's most efficient GPT model tier for focused, high-volume tasks.
2 releases
GPT Astra
OpenAI's highest-capability GPT model tier.
1 release
- This page6Current. In 6 products we coverPrice$10 / $50Speed71 tok/s
GPT-5
OpenAI's GPT-5 frontier models, released before the Sol, Terra and Luna tiers.
2 releases
gpt-oss
OpenAI's open-weight GPT models under the Apache 2.0 license.
1 release
GPT Codex
OpenAI's GPT models tuned for agentic coding in Codex.
1 release
Where it fits
The layers of Agentic Software Development that GPT-6 Astra can power. A product supplies the rest.
Product & Engineering, Software Development
Agentic Software Development
- Primary role
- Foundation Model / Reasoning Engine
GPT-6 Astra can power coding, reasoning, and validation work inside an agentic software-development product. The Model does not itself provide the surrounding interface, execution environment, or system of record.
- Supporting
Work planning & task decomposition
The Model can assist with work planning & task decomposition when a Product supplies the necessary context and tools.
- Strong fit
Codebase context & intelligence
The provider documents long-context or codebase-oriented reasoning suitable for this layer. OpenAI's page
- Strong fit
Coding & implementation
The provider documents this Model for software-engineering and coding work. OpenAI's page
- Supporting
Debugging & investigation
The Model can assist with debugging & investigation when a Product supplies the necessary context and tools.
- Supporting
Testing & verification
The Model can assist with testing & verification when a Product supplies the necessary context and tools.
- Supporting
Code review & quality
The Model can assist with code review & quality when a Product supplies the necessary context and tools.
Products
We cover 6 products that offer GPT-6 Astra today: 5 subscriptions and 1 API.
Through a subscription
- OpenCode+27 PositiveOpen-source, MIT-licensed coding agent that edits code and runs commands from a terminal UI, desktop app, web client, or editor extension.
- GitHub Copilot+15 MixedGitHub's AI coding agents, IDE assistance, and pull request review.
- ChatGPT+14 MixedOpenAI's general-purpose AI assistant for individuals and organizations.
- Codex+55 Strong positiveOpenAI's coding agent for cloud, terminal, IDE, and app workflows.
- Perplexity−25 NegativeAI answer engine with cited web research, model choice, and an agent for longer tasks.
Through an API
Limits each vendor states
- GitHub CopilotCopilot Pro+, Copilot Max, Copilot Business, Copilot Enterprise
- Included on the Copilot plans listed. Copilot Free and Copilot Student get auto model selection only, so they cannot pick it.
- ChatGPTPlus, Pro
- Included on Plus, with expanded access on Pro, where Pro reasoning runs on GPT-6 Astra.
- CodexPlus, Business
- 5-45 local messages per five-hour period on Plus and Standard Business (estimate); Pro plans currently have no five-hour limit; in Work and Codex
- PerplexityMax
- In Perplexity's Search model picker on Max, not on Pro; usage limits apply, with no per-model figures published.
Plan access as each vendor's page states it: GitHub (Oct 31, 2026), OpenAI, chatgpt.com (Oct 28, 2026), OpenAI, learn.chatgpt.com (Oct 28, 2026), Perplexity (Oct 26, 2026).
Comparisons
GILD comparisons that name GPT-6 Astra, then those of the clouds and APIs that serve it.
- Amp vs Claude Code: Routed Models and Orbs, or Anthropic's Own Agent?Names GPT-6 Astra
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Names GPT-6 Astra
- Claude Code vs Codex: Which Agentic Coding Workflow Fits Your Team?Names GPT-6 Astra
- Gemini API vs Amazon Bedrock: One Model Family or a Model Marketplace?Names GPT-6 Astra
- Gemini CLI vs Codex: Google Cloud Billing or ChatGPT Plan?Names GPT-6 Astra
- OpenAI API vs Azure OpenAI: Same Models, Different ContractsNames GPT-6 Astra
- OpenAI API vs Gemini API: Who Finishes the Task for Less?Names GPT-6 Astra
- Perplexity vs ChatGPT: Cited Research or a General Work Assistant?Names GPT-6 Astra
- Amazon Bedrock vs Claude API: Buying Claude Through AWS or From AnthropicCompares routes that serve GPT-6 Astra
- Amazon Bedrock vs Microsoft Foundry: Which Cloud AI Platform Fits Your Stack?Compares routes that serve GPT-6 Astra
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve GPT-6 Astra
- Gemini Enterprise Agent Platform vs Microsoft Foundry: Google Cloud or Azure for Models and AgentsCompares routes that serve GPT-6 Astra
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve GPT-6 Astra
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Compares routes that serve GPT-6 Astra
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve GPT-6 Astra
What practitioners report
Strongest on Tool use and structured output, weakest on Reliability.
Each figure is the share of accounts naming GPT-6 Astra that speak well of it on that axis. An axis is scored once praise and concerns are both on record from at least five accounts by three authors. An account from the maker, a company that sells or serves the model, or the maker's expert program is listed and counts toward no figure.
| Axis | Favorable | Accounts |
|---|---|---|
| Quality and reasoningWhether its answers and code are right on the author's own task: reasoning, accuracy, instruction following, and consistency. | 44% | 12 favorable, 15 not, 26 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 62% | 8 favorable, 5 not, 13 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | 27% | 3 favorable, 8 not, 11 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | 41% | 7 favorable, 10 not, 17 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 29% | 7 favorable, 17 not, 23 authors |
| SpeedResponse time, time to first token, and throughput. | 41% | 7 favorable, 10 not, 17 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 14% | 2 favorable, 12 not, 14 authors |
Every model on these seven axes
| Axis | GPT-6 Astra | GPT-6.1 Terra | GPT-6.1 Sol | GPT-6 Luna | GPT-5.6 Sol | GPT-5.6 Terra | GPT-5.6 Luna | GPT-5.5 | GPT-5.4 | gpt-oss-120b | GPT-6 Sol | GPT-5.3-Codex | Claude Haiku 5.5 | Claude Sonnet 5.5 | Claude Opus 5.5 | Claude Fable 5.1 | Claude Opus 5 | Claude Sonnet 5 | Claude Fable 5 | Claude Opus 4.8 | Claude Opus 4.7 | Claude Sonnet 4.6 | Claude Opus 4.6 | Claude Opus 4.5 | Claude Haiku 4.5 | Claude Sonnet 4.5 | Gemini 4 Argon | Gemini 3.8 Flash | Gemma 4 31B | Gemini 3.1 Pro Preview | Gemini 3.6 Flash | DeepSeek V4.1 Flash | DeepSeek V4 Pro | Kimi K3.1 Pro | Kimi K3 | Kimi K2.7 Code | Mistral Large 4 | Mistral Medium 3.5 | Grok 4.7 | Grok 4.6 | Grok 4.5 | MiniMax M3.1 Flash | Mercury 3 | GLM-5.3-Flash | GLM-5.3 | GLM-5.2 | Muse Spark Open | Muse Wonder | Muse Spark 1.3 | Llama 4 Scout | Llama 4 Maverick | Qwen3.8 27B | Qwen3.8 Max | MiMo-V2.6-Pro | MiMo-V2.6-Flash | Ling 3.1 Flash | Step 5 Preview |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Quality and reasoning | 44%12 favorable, 15 not, 26 authors | 33%3 favorable, 6 not, 8 authors | 55%12 favorable, 10 not, 22 authors | 55%16 favorable, 13 not, 29 authors | 33%3 favorable, 6 not, 9 authors | 38%3 favorable, 5 not, 8 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 33%4 favorable, 8 not, 12 authors | 33%2 favorable, 4 not, 6 authors | 58%22 favorable, 16 not, 38 authors | 31%10 favorable, 22 not, 32 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 73%19 favorable, 7 not, 26 authors | 64%14 favorable, 8 not, 22 authors | 68%17 favorable, 8 not, 25 authors | 54%15 favorable, 13 not, 28 authors | 50%6 favorable, 6 not, 12 authors | 56%9 favorable, 7 not, 16 authors | 68%13 favorable, 6 not, 18 authors | 68%17 favorable, 8 not, 25 authors | 57%12 favorable, 9 not, 21 authors | 67%12 favorable, 6 not, 18 authors | 70%19 favorable, 8 not, 27 authors | 62%13 favorable, 8 not, 20 authors | 58%14 favorable, 10 not, 24 authors | 69%11 favorable, 5 not, 16 authors | 63%22 favorable, 13 not, 35 authors | 56%27 favorable, 21 not, 45 authors | 80%24 favorable, 6 not, 28 authors | 56%20 favorable, 16 not, 36 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 61%25 favorable, 16 not, 40 authors | Only concerns on record0 favorable, 4 not, 4 authors | 59%20 favorable, 14 not, 32 authors | Only praise on record3 favorable, 0 not, 3 authors | 50%3 favorable, 3 not, 6 authors | 58%11 favorable, 8 not, 18 authors | 36%5 favorable, 9 not, 14 authors | 43%16 favorable, 21 not, 36 authors | 86%6 favorable, 1 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 62%13 favorable, 8 not, 21 authors | 86%18 favorable, 3 not, 21 authors | 67%14 favorable, 7 not, 21 authors | 76%47 favorable, 15 not, 61 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record2 favorable, 0 not, 2 authors | 53%8 favorable, 7 not, 15 authors | 44%8 favorable, 10 not, 17 authors | 71%24 favorable, 10 not, 34 authors | 57%4 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors |
| Tool use and structured output | 62%8 favorable, 5 not, 13 authors | 40%2 favorable, 3 not, 5 authors | 40%4 favorable, 6 not, 10 authors | 33%3 favorable, 6 not, 9 authors | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | No accounts yet | 27%4 favorable, 11 not, 15 authors | 56%5 favorable, 4 not, 9 authors | No accounts yet | 67%6 favorable, 3 not, 9 authors | 40%4 favorable, 6 not, 10 authors | 46%6 favorable, 7 not, 13 authors | 30%3 favorable, 7 not, 10 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 70%7 favorable, 3 not, 10 authors | 57%4 favorable, 3 not, 7 authors | 50%4 favorable, 4 not, 8 authors | 50%4 favorable, 4 not, 8 authors | 29%2 favorable, 5 not, 7 authors | 33%4 favorable, 8 not, 12 authors | 70%7 favorable, 3 not, 10 authors | 43%3 favorable, 4 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 25%2 favorable, 6 not, 8 authors | 47%7 favorable, 8 not, 15 authors | 67%4 favorable, 2 not, 6 authors | 54%7 favorable, 6 not, 12 authors | Only concerns on record0 favorable, 1 not, 1 author | 59%10 favorable, 7 not, 17 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 38%5 favorable, 8 not, 13 authors | Only concerns on record0 favorable, 5 not, 5 authors | 38%6 favorable, 10 not, 16 authors | Only praise on record2 favorable, 0 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | 67%4 favorable, 2 not, 6 authors | 80%8 favorable, 2 not, 10 authors | 33%2 favorable, 4 not, 6 authors | 57%4 favorable, 3 not, 7 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only concerns on record0 favorable, 4 not, 4 authors | 46%6 favorable, 7 not, 13 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 5 not, 5 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author |
| Long context | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 1 not, 1 author | 38%3 favorable, 5 not, 8 authors | 20%1 favorable, 4 not, 5 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 25%2 favorable, 6 not, 8 authors | Only concerns on record0 favorable, 3 not, 3 authors | No accounts yet | 29%2 favorable, 5 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 80%8 favorable, 2 not, 10 authors | 63%5 favorable, 3 not, 8 authors | 67%4 favorable, 2 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 33%2 favorable, 4 not, 6 authors | 60%6 favorable, 4 not, 10 authors | 50%4 favorable, 4 not, 7 authors | 71%5 favorable, 2 not, 7 authors | 64%7 favorable, 4 not, 11 authors | 40%4 favorable, 6 not, 10 authors | 40%2 favorable, 3 not, 5 authors | 50%4 favorable, 4 not, 8 authors | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 20%1 favorable, 4 not, 5 authors | 44%7 favorable, 9 not, 16 authors | Only praise on record1 favorable, 0 not, 1 author | 58%7 favorable, 5 not, 12 authors | No accounts yet | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | No accounts yet | 42%5 favorable, 7 not, 12 authors | No accounts yet | No accounts yet | 40%2 favorable, 3 not, 5 authors | 60%3 favorable, 2 not, 5 authors | No accounts yet | 40%2 favorable, 3 not, 5 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 3 not, 3 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 75%6 favorable, 2 not, 8 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | No accounts yet |
| Developer experience | 41%7 favorable, 10 not, 17 authors | Only concerns on record0 favorable, 2 not, 2 authors | 27%3 favorable, 8 not, 11 authors | 25%2 favorable, 6 not, 8 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet | No accounts yet | 14%1 favorable, 6 not, 7 authors | 25%3 favorable, 9 not, 12 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 38%6 favorable, 10 not, 16 authors | 50%7 favorable, 7 not, 14 authors | 25%3 favorable, 9 not, 12 authors | 29%2 favorable, 5 not, 7 authors | 25%3 favorable, 9 not, 12 authors | 53%10 favorable, 9 not, 19 authors | 29%4 favorable, 10 not, 14 authors | 57%4 favorable, 3 not, 7 authors | 45%5 favorable, 6 not, 11 authors | 67%8 favorable, 4 not, 12 authors | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | 50%3 favorable, 3 not, 6 authors | 33%3 favorable, 6 not, 9 authors | 39%7 favorable, 11 not, 17 authors | Only concerns on record0 favorable, 7 not, 7 authors | 40%8 favorable, 12 not, 20 authors | No accounts yet | 35%8 favorable, 15 not, 23 authors | No accounts yet | 9%1 favorable, 10 not, 11 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | 13%2 favorable, 14 not, 16 authors | Only concerns on record0 favorable, 9 not, 9 authors | 25%5 favorable, 15 not, 20 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 7 not, 7 authors | 11%1 favorable, 8 not, 9 authors | Only concerns on record0 favorable, 3 not, 3 authors | 33%5 favorable, 10 not, 15 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 6 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet |
| Cost | 29%7 favorable, 17 not, 23 authors | 80%8 favorable, 2 not, 9 authors | 74%14 favorable, 5 not, 19 authors | 79%22 favorable, 6 not, 26 authors | 57%4 favorable, 3 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | 50%3 favorable, 3 not, 6 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%5 favorable, 3 not, 8 authors | 60%3 favorable, 2 not, 5 authors | 55%12 favorable, 10 not, 21 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 69%20 favorable, 9 not, 29 authors | 45%10 favorable, 12 not, 22 authors | 56%15 favorable, 12 not, 27 authors | 20%4 favorable, 16 not, 20 authors | 43%3 favorable, 4 not, 7 authors | 39%7 favorable, 11 not, 17 authors | 8%1 favorable, 11 not, 12 authors | 40%6 favorable, 9 not, 14 authors | 50%7 favorable, 7 not, 13 authors | 50%6 favorable, 6 not, 12 authors | 33%7 favorable, 14 not, 20 authors | 53%8 favorable, 7 not, 15 authors | 29%4 favorable, 10 not, 12 authors | 38%3 favorable, 5 not, 8 authors | 35%7 favorable, 13 not, 20 authors | 58%14 favorable, 10 not, 23 authors | Only praise on record7 favorable, 0 not, 7 authors | 50%8 favorable, 8 not, 16 authors | Only concerns on record0 favorable, 1 not, 1 author | 66%25 favorable, 13 not, 37 authors | Only praise on record2 favorable, 0 not, 2 authors | 40%10 favorable, 15 not, 25 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 8 not, 8 authors | 19%5 favorable, 21 not, 26 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record4 favorable, 0 not, 4 authors | 80%12 favorable, 3 not, 15 authors | 50%6 favorable, 6 not, 12 authors | 76%16 favorable, 5 not, 21 authors | 35%8 favorable, 15 not, 23 authors | 71%5 favorable, 2 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | Only concerns on record0 favorable, 2 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only praise on record3 favorable, 0 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author |
| Speed | 41%7 favorable, 10 not, 17 authors | 83%5 favorable, 1 not, 5 authors | 37%7 favorable, 12 not, 19 authors | 45%5 favorable, 6 not, 11 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 80%4 favorable, 1 not, 5 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | 85%23 favorable, 4 not, 27 authors | 57%4 favorable, 3 not, 7 authors | Only praise on record1 favorable, 0 not, 1 author | 74%14 favorable, 5 not, 19 authors | 88%14 favorable, 2 not, 16 authors | 46%6 favorable, 7 not, 13 authors | 44%4 favorable, 5 not, 9 authors | 60%3 favorable, 2 not, 5 authors | 44%4 favorable, 5 not, 9 authors | 57%4 favorable, 3 not, 7 authors | 31%4 favorable, 9 not, 13 authors | 63%5 favorable, 3 not, 8 authors | 17%1 favorable, 5 not, 6 authors | 36%4 favorable, 7 not, 11 authors | 73%8 favorable, 3 not, 11 authors | 78%7 favorable, 2 not, 9 authors | 75%6 favorable, 2 not, 8 authors | 45%5 favorable, 6 not, 11 authors | 61%19 favorable, 12 not, 31 authors | 53%10 favorable, 9 not, 17 authors | 35%6 favorable, 11 not, 16 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 68%21 favorable, 10 not, 30 authors | Only concerns on record0 favorable, 1 not, 1 author | 21%4 favorable, 15 not, 19 authors | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | 21%3 favorable, 11 not, 14 authors | Only concerns on record0 favorable, 2 not, 2 authors | 29%5 favorable, 12 not, 17 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only praise on record2 favorable, 0 not, 2 authors | 44%4 favorable, 5 not, 9 authors | 65%13 favorable, 7 not, 20 authors | 33%3 favorable, 6 not, 9 authors | 20%3 favorable, 12 not, 15 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | No accounts yet | 33%7 favorable, 14 not, 21 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author |
| Reliability | 14%2 favorable, 12 not, 14 authors | Only concerns on record0 favorable, 1 not, 1 author | 13%1 favorable, 7 not, 8 authors | Only concerns on record0 favorable, 5 not, 5 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 3 not, 3 authors | 20%1 favorable, 4 not, 5 authors | 18%2 favorable, 9 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 9%1 favorable, 10 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 63%5 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 17%2 favorable, 10 not, 12 authors | 18%2 favorable, 9 not, 11 authors | 17%1 favorable, 5 not, 6 authors | 20%3 favorable, 12 not, 15 authors | 38%6 favorable, 10 not, 16 authors | 29%2 favorable, 5 not, 7 authors | 40%4 favorable, 6 not, 10 authors | 5%1 favorable, 18 not, 19 authors | 15%3 favorable, 17 not, 20 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%3 favorable, 19 not, 22 authors | Only concerns on record0 favorable, 1 not, 1 author | 42%5 favorable, 7 not, 12 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 8%1 favorable, 12 not, 13 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 38%3 favorable, 5 not, 8 authors | Only concerns on record0 favorable, 4 not, 4 authors | 22%2 favorable, 7 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 60%3 favorable, 2 not, 5 authors | 33%2 favorable, 4 not, 5 authors | Only concerns on record0 favorable, 7 not, 7 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author |
The 89 accounts behind GPT-6 Astra's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis and the web for accounts that name GPT-6 Astra.
Quality and reasoning 44%
- Favorable
It's the new frontier model by a landslide
Comment on "An Alien Mind". gertlabs, account that runs Gert Labs multi-agent coding evaluations (stated in the comment), self-described, Sep 6, 2026. GPT-6 Astra in 100 multi-agent coding environments via the OpenAI Flex endpoint on OpenRouter.
- Favorable
Both Astra and 6.1-Sol are pretty comfortably ahead of Opus 5.5 in these types of evaluations
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". gertlabs, account that runs Gert Labs coding evaluations (stated in the comment), self-described, Sep 30, 2026. GPT-6 Astra and GPT-6.1 Sol across 100 unsaturated coding and engineering environments, API usage.
- Unfavorable
scores the least of the three, and the UI is full of slop copy and design
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". thefourthchime, Hacker News commenter who ran a Pac-Man bake-off, self-described, Sep 29, 2026. GPT-6 Astra on a Pac-Man build bake-off.
- Favorable
Astra has been the best model for this flow so far
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". jjcm, Hacker News commenter testing image-to-HTML builds, self-described, Sep 29, 2026. GPT-6 Astra on an image-to-HTML build flow.
- Favorable
GPT 6 Astra can easily produce a TLA+ model that can be verified under very real-world system model assumptions
Comment on "From the creator of Redis; run LLM locally with ds4". antirez, Hacker News commenter, self-described, Oct 5, 2026. GPT-6 Astra producing a TLA+ model of RedLock.
- Unfavorable
if I'd rate Fable's performance at 7/10 (subjective scoring), Astra would be 2/10
Comment on "The gap in shared understanding of LLM capability is widening". roncesvalles, Hacker News commenter, self-described, Oct 12, 2026. GPT-6 Astra on a personal sociology benchmark.
- Unfavorable
its coding capabilities actually seem worse than SOL in many cases
Comment on "My First Week with GPT-6 Astra". jdw64, Hacker News commenter and subcontract developer (stated in another comment), self-described, Sep 13, 2026. GPT-6 Astra after switching from GPT-5.6 Sol for coding.
- Unfavorable
It really doesn't seem to be better than 5.5 at most programming jobs
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". moshegramovsky, Hacker News commenter on a $200 OpenAI plan, self-described, Sep 29, 2026. GPT-6 Astra high thinking on a complex infra project across a large codebase.
- Favorable
while being a significant leap in capabilities & higher-level thinking
Comment on "GPT-6 Astra". dannyw, Hacker News commenter and external early tester (stated in the comment), self-described, Sep 4, 2026. GPT-6 Astra in Codex CLI during early external testing.
- Unfavorable
Other stuff like complex coding problems in an existing codebase it stumbles more often than not
Comment on "GPT-6 Astra on robot arms". enraged_camel, Hacker News commenter, self-described, Sep 6, 2026. GPT-6 Astra on complex coding in an existing codebase.
- Favorable
I didn't do a ton work to document and measure the specifics, but it was very impressive
Comment on "Analyzing Frontier Model Progress with My Favourite Game: Prince of Persia". criemen, Hacker News commenter, self-described, Sep 26, 2026. GPT-6 Astra hill-climbing an Asteroids client task.
- Unfavorable
in cyber security and reverse engineering it is falling behind by a lot compared to 5.6 cyber
Comment on "Ask HN: Initial Thoughts on GPT-6 Astra?". Alhaji123, Hacker News commenter in the Daybreak program (stated in the comment), self-described, Sep 6, 2026. GPT-6 Astra under Daybreak on reverse engineering.
- Favorable
Astra is state-of-the-art on most robotics benchmarks
Comment on "Astra as a Robotics World Model". quantbagel, Hacker News commenter who distilled Astra into a world model (stated in the comment), self-described, Oct 2, 2026. GPT-6 Astra on robotics benchmarks.
- Unfavorable
GPT-5.6 Sol and GPT-6 Astra both do this on the regular when trying to safe an ancient, utterly messed up git tree
Comment on "I quit OpenAI because its culture is broken". Topfi, Hacker News commenter who runs personal model evals (stated in the comment), self-described, Oct 4, 2026. GPT-6 Astra on git disaster-recovery evals.
- Unfavorable
Tried again a simple coding task with Astra maxed out. I did it only partially, left memory leak and hanging pointer
Comment on "Astra for Law". varispeed, Hacker News commenter, self-described, Sep 18, 2026. GPT-6 Astra maxed out on coding and a long legal document.
- Favorable
this is very impressive with Astra. I've had no issues with either
Comment on "Astra for Law". Gareth321, Hacker News commenter, self-described, Sep 18, 2026. GPT-6 Astra reading digital and scanned PDFs.
- Favorable
Astra medium effort consistently catches more issues than Sol 5.6
Comment on "Everyone should slow down AI development except for me". sampullman, Hacker News commenter who runs a review bot, self-described, Sep 13, 2026. GPT-6 Astra medium effort in a code review bot.
- Unfavorable
Opus 5.5 xhigh made great progress on the task, more so than Astra High
Comment on "Claude Code reads AGENTS.md only when telemetry is on [fixed]". user43928, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Astra High in the Codex app.
- Favorable
Astra was/is superior for planning type tasks
Comment on "GPT-6 Sol and Luna". cmrdporcupine, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra for planning and UI work.
- Favorable
Astra's was better, but Sol didn't do so bad
Comment on "Why isn't the industry freaking out about DeepSeek 4.1 Flash?". Quothling, Hacker News commenter, self-described, Oct 8, 2026. GPT-6 Astra in Copilot cowork on one coding task, compared with Sol and Fable.
- Unfavorable
how awful and incompetent GPT 6 Astra had been for me
Comment on "A Series of Unfortunate Events for OpenAI Users". GaryBluto, Hacker News commenter, self-described, Oct 6, 2026. GPT-6 Astra in Codex over 20 days.
- Unfavorable
I actually started with 6.1 Sol and 6 Astra but pulled them after a week of little progress
Comment on "Show HN: Gemini 4 Argon plays StarCraft". t1amat, Hacker News commenter building game-server bots, self-described, Oct 16, 2026. GPT-6 Astra on a ModernUO bot project.
- Unfavorable
Repeated scope drift, unauthorized changes to requirements, and false-positive completion reporting
Repeated instruction-following failures and false task completion: Codex CLI / GPT-6 Astra Max. manuelpaulo, GitHub user on Plus filing on openai/codex, self-described, Oct 21, 2026. GPT-6 Astra, reasoning effort Max, in Codex CLI 0.162.1.
- Unfavorable
the model interpreted agreement with the final interview answer as authorization to implement and made extensive code changes
grill-with-docs: gpt-6-Astra-low skips to-spec and to-tickets. lawrenceg4, GitHub user filing on mattpocock/skills, self-described, Sep 10, 2026. GPT-6 Astra low (gpt-6-Astra-low) running the grill-with-docs skill.
- Unfavorable
Astra cannot reliably convert the target position in RGB observations into accurate MuJoCo world coordinates
FluxVLA + GPT-6 Astra: Unreliable Spatial Grounding in LIBERO. ffffox7961, GitHub user filing on FluxVLA, self-described, Sep 15, 2026. GPT-6 Astra through the OpenAI Responses API in a FluxVLA LIBERO robot pipeline.
- Unfavorable
GPT-6 Astra Max still feels less reliable than 6.1 Sol Max for real coding work
GPT-6 Astra Max still feels less reliable than 6.1 Sol Max. mikechaves_io, creative director and creative technologist (stated in X bio), self-described, Oct 20, 2026. GPT-6 Astra Max for real coding work against GPT-6.1 Sol Max.
- Favorable
Astra pinpointed exactly 3 critical issues and gave an honest assessment of what had been done right
First impressions of GPT-6 Astra. Gegam245074, engineering manager (stated in X bio), self-described, Sep 4, 2026. GPT-6 Astra at xhigh for code review and coding.
Tool use and structured output 62%
- Favorable
it's a good coordinator but even more cost
Comment on "Astra for Coding: Why Are We Doing This Again?". AmazingTurtle, Hacker News commenter, self-described, Sep 11, 2026. GPT-6 Astra in Codex on a subscription, rebasing and test-fixing tasks.
- Favorable
a main agentic model like Opus 5.5 or GPT-6 Astra are, which can actually do things that function properly without much fidgeting or intervention
Comment on "DeepInfer: High-performance inference framework for DeepSeek models". XCSme, Hacker News commenter, self-described, Oct 20, 2026. GPT-6 Astra as a main agentic model.
- Favorable
better subagent orchestration; better and more reliable tool use
Comment on "David Sacks: OpenAI and Anthropic Don't Need Regulations to Pace Frontier Models". threecheese, Hacker News commenter, self-described, Sep 13, 2026. GPT-6 Astra for computer use, 3D modeling, subagents and coding.
- Favorable
Astra does such a good work with SketchUp 2026 and computer use
Comment on "Cartesian – AI 3D Modeling for Design". Ciantic, Hacker News commenter, self-described, Sep 15, 2026. GPT-6 Astra with computer use in SketchUp 2026.
- Favorable
place components and route traces out of the box, just via normal 'computer use'
Comment on "Show HN: Copperhead – Hardware as Fast as Software". avsteele, Hacker News commenter, self-described, Sep 8, 2026. GPT-6 Astra through computer use on schematics and PCB routing.
- Favorable
Codex Astra can do a great-(ish) job as a project coordinator dispatching tasks to a pool of 6.1 Sol sub agents
Comment on "Why are coding agents so dumb?". Rapzid, Hacker News commenter experienced in context engineering (stated in the comment), self-described, Oct 9, 2026. GPT-6 Astra in Codex as coordinator of GPT-6.1 Sol subagents.
- Favorable
Astra planner/designer with Sol+Luna subagents has worked well for me
Comment on "GPT-6 Sol and Luna". rbranson, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra as planner with Sol and Luna subagents in Codex.
- Favorable
I have been able to get GPT 6 Astra to do this more successfully
Comment on "Sonnet 5.5". shepherdjerred, Hacker News commenter on Codex and Claude Code $200 plans, self-described, Sep 29, 2026. GPT-6 Astra in Codex dividing large work across cheaper subagents.
- Unfavorable
the model returned an otherwise complete JSON final response but omitted the final `]}` delimiters
[CLI] GPT-6 Astra intermittently returns completed final JSON missing terminal ]}. Bateriusz, GitHub user filing on openai/codex, self-described, Oct 17, 2026. GPT-6 Astra (gpt-6-astra-high) in Codex CLI 0.162.1 as a non-interactive JSON reviewer.
- Unfavorable
gpt-6-astra / max | run's schema, unchanged | fails with `max_output_tokens`
[Bug] Coordinator finalize blocks deterministically with max_output_tokens on a specific verification_evidence enum. JFusco, maintainer of agent-review-workflows on GitHub, self-described, Oct 26, 2026. GPT-6 Astra (gpt-6-astra, max and high) in a Codex coordinator with an output schema.
- Unfavorable
it looped for 4 - 6 hours and did not complete the task
GPT-6 Astra Loop/Long hours. Jibri86, GitHub user filing on openai/codex, self-described, Sep 5, 2026. GPT-6 Astra (gpt-6-astra) in Codex CLI 0.153.3 on Plus.
- Unfavorable
It then entered a repeated refusal loop and would not even attempt an already-created, explicitly authorized, exact-allowlist PowerShell cleanup script
GPT-6 Astra max turns one deletion-command rejection into a false permanent refusal loop. oyasumiaiko, GitHub user on ChatGPT Pro filing on openai/codex, self-described, Oct 22, 2026. GPT-6 Astra max in the Codex App on Windows.
- Unfavorable
GPT-6 Astra repeatedly stopped authorized command work while safe investigation or implementation remained available
Prevent premature GPT-6 Astra stops and make command halts actionable. LeanAndMean, maintainer of scramjet on GitHub, self-described, Sep 9, 2026. GPT-6 Astra (github-copilot/gpt-6-astra) running agent commands in scramjet.
Long context 27%
- Unfavorable
6 Astra lost the most key details of a project across a compaction and got confused about what we were actually trying to do
Comment on "Gemini 4 Argon". macNchz, Hacker News commenter, self-described, Sep 30, 2026. GPT-6 Astra in a long session with compaction.
- Unfavorable
it happens so frequently that even a model as powerful as Astra sometimes loses the plot on long-running tasks
Comment on "GPT-6 Sol and Luna". jeffnash, Hacker News commenter on Codex Pro 20x, self-described, Sep 22, 2026. GPT-6 Astra in Codex and ChatGPT on the Codex Pro 20x plan.
- Unfavorable
in my personal greenfield project Astra keeps compacting all the time, to the point of it being unusable
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". kaoD, Hacker News commenter, self-described, Sep 30, 2026. GPT-6 Astra on a personal greenfield project.
- Unfavorable
Constantly compacting
Comment on "GPT-6 Sol and Luna". jorl17, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra at High and Max.
- Unfavorable
It was absolutely terrible on a few long running tasks (~2 hours each)
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". moshegramovsky, Hacker News commenter on a $200 OpenAI plan, self-described, Sep 29, 2026. GPT-6 Astra high thinking on a complex infra project across a large codebase.
- Favorable
I had a long running autonomous Astra session today that got to about 600k and it finished fine with everything I asked it to do solved nicely
Comment on "Notes on gotchas while migrating 35kb preprompts from Opus to self-hosted Ollama". birdsongs, Hacker News commenter, self-described, Sep 14, 2026. GPT-6 Astra in a long autonomous session.
- Favorable
By the time it has done a dozen or so compactions, it fully understands the work I want it to do
Comment on "GPT-6 Sol and Luna". erichocean, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra in Codex across hundreds of compactions.
- Favorable
has worked well for me to improve context continuity
Comment on "GPT-6 Sol and Luna". rbranson, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra as planner with Sol and Luna subagents in Codex.
- Unfavorable
I then tried Astra on farily long legal document to produce an excerpt. The excerpt had wrong conclusion and logical errors
Comment on "Astra for Law". varispeed, Hacker News commenter, self-described, Sep 18, 2026. GPT-6 Astra maxed out on coding and a long legal document.
- Unfavorable
In a long-lived ChatGPT Work thread, the user repeatedly experienced turns making no visible progress under GPT-6 Astra
ChatGPT Work long thread stops progressing under GPT-6 Astra; resumes after switching to Sol. eddyaba01, GitHub user filing on openai/codex, self-described, Oct 20, 2026. GPT-6 Astra in a long-lived ChatGPT Work thread.
- Unfavorable
Context compaction fails intermittently with `openai/gpt-6-astra` at `max` reasoning
Compaction hits summary output cap with GPT-6 Astra at max reasoning. tianrendong, GitHub user filing on earendil-works/pi, self-described, Sep 12, 2026. GPT-6 Astra (openai/gpt-6-astra) at max reasoning in the pi coding agent 0.85.1.
Developer experience 41%
- Unfavorable
it constantly scope creeps itself with "yet another thing" to give it that darn polished lick
Comment on "Astra for Coding: Why Are We Doing This Again?". AmazingTurtle, Hacker News commenter, self-described, Sep 11, 2026. GPT-6 Astra in Codex on a subscription, rebasing and test-fixing tasks.
- Unfavorable
It takes a lot of steering to keep it from adding a bunch of, while useful, features that are not strictly enough to the point
Comment on "Pop!_OS bans AI-generated code from much of its codebase". williamcotton, Hacker News commenter, self-described, Oct 3, 2026. GPT-6 Astra High on a project built entirely with it.
- Unfavorable
it refactored the shit out of it claiming all sorts of stuff without even asking about the context
Comment on "Coding is not solved". necovek, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Astra in Codex reviewing a benchmarking script.
- Favorable
Sol and Astra are by far the best of the models I use at following the instructions in AGENTS.md
Comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". RussianCow, Hacker News commenter, self-described, Oct 24, 2026. GPT-6 Astra following AGENTS.md instructions.
- Favorable
Astra is also excellent at instruction following and respecting the guidance and steers boundaries you have
Comment on "GPT-6 Astra". dannyw, Hacker News commenter and external early tester (stated in the comment), self-described, Sep 4, 2026. GPT-6 Astra in Codex CLI during early external testing.
- Favorable
I haven't felt similar issues with GPT 6 though and am very happy with Astra low/med/high as my default choices depending on the task
Comment on "GPT-6 Sol and Luna". superfrank, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra at low, medium and high effort.
- Favorable
Astra could actually be steered into a direction I want and it provides valuable/insightful feedback
Comment on "GPT-6 Astra". rafaelmn, Hacker News commenter, self-described, Sep 5, 2026. GPT-6 Astra on a technical problem compared with Gemini Flash 3.8.
- Favorable
Astra's outputs are much more concise while being similarly accurate
Comment on "Ask HN: What default model do you use and why?". asd88, Hacker News commenter with metered tokens at work, self-described, Sep 12, 2026. GPT-6 Astra at work after switching from Claude Opus and Fable.
- Unfavorable
With Astra, it's like pulling teeth. It often does not understand what I'm trying to do, takes things literally
Comment on "Real-SWE: Benchmarking AI models on private, real-world, enterprise codebases". enraged_camel, Hacker News commenter, self-described, Sep 12, 2026. GPT-6 Astra on agentic coding tasks compared with Fable.
- Favorable
I have personally encountered GPT-6 Astra ask these exact questions before proceeding
Comment on "I'm sorry, but you still have to think". heaney-555, Hacker News commenter, self-described, Oct 11, 2026. GPT-6 Astra in Codex.
- Unfavorable
GPT-6 Astra (on Light) stops a lot and often in unintuitive ways that I haven't seen in a while
Comment on "Ask HN: Initial Thoughts on GPT-6 Astra?". Topfi, Hacker News commenter who runs personal model evals (stated in comments), self-described, Sep 5, 2026. GPT-6 Astra (on Light) in the Codex app with voice and computer use.
- Unfavorable
I've had to tell it to stop zooming off and doing things, calling loads of tools and looking up websites
Comment on "Plan mode is dead". robertlagrant, Hacker News commenter on the £20 subscription, self-described, Sep 26, 2026. GPT-6 Astra for homelab work on a £20 subscription.
- Unfavorable
the preflight check fails because this model doesn't support the `temperature` parameter, preventing the server from starting
[BUG]: GPT-6-Astra model doesn't support temperature parameter - prevents server startup. Ed-Jaramillo, maintainer of loom on GitHub, self-described, Oct 22, 2026. GPT-6 Astra (bedrock/us.openai.gpt-6-astra) through Amazon Bedrock.
- Unfavorable
OpenAI rejects that parameter for this model and requires `max_completion_tokens` instead
fix: support GPT-6 Astra's completion-token parameter. RyanAOGallagher, GitHub user filing on charmbracelet/crush, self-described, Sep 8, 2026. GPT-6 Astra (gpt-6-astra) through the OpenAI provider in Crush v0.92.0.
- Unfavorable
The bridge sends `reasoning.effort: "none"`, a level Astra does not have
[Bug]: Bedrock GPT-6 Astra returns 400 on /v1/messages when thinking is disabled. kimnamu, GitHub user filing on BerriAI/litellm, self-described, Sep 24, 2026. GPT-6 Astra on Bedrock Converse and Mantle through LiteLLM.
- Unfavorable
GPT-6 Astra is so unreliable I have to be so precise with my prompts b/c you can trust on it to misinterpret anything that isn't directly stated
GPT-6 Astra is so unreliable. lehoho248, building an AI media studio, Carnegie Mellon Engineering (stated in X bio), self-described, Oct 21, 2026. GPT-6 Astra on prompts for product work.
- Favorable
First impressions of GPT-6 Astra 1. A very terse model
First impressions of GPT-6 Astra. Gegam245074, engineering manager (stated in X bio), self-described, Sep 4, 2026. GPT-6 Astra at xhigh for code review and coding.
Cost 29%
- Favorable
it was also ~80% cheaper and 30% faster in agentic coding
Comment on "An Alien Mind". gertlabs, account that runs Gert Labs multi-agent coding evaluations (stated in the comment), self-described, Sep 6, 2026. GPT-6 Astra in 100 multi-agent coding environments via the OpenAI Flex endpoint on OpenRouter.
- Favorable
both end up being cheaper than Opus via API usage
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". gertlabs, account that runs Gert Labs coding evaluations (stated in the comment), self-described, Sep 30, 2026. GPT-6 Astra and GPT-6.1 Sol across 100 unsaturated coding and engineering environments, API usage.
- Unfavorable
Astra costs the most, scores the least of the three
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". thefourthchime, Hacker News commenter who ran a Pac-Man bake-off, self-described, Sep 29, 2026. GPT-6 Astra on a Pac-Man build bake-off.
- Unfavorable
There is a massive gap in token pricing between GPT-5.2 and GPT-6 Astra, yet the actual leap in quality feels negligible
Comment on "My First Week with GPT-6 Astra". jdw64, Hacker News commenter and subcontract developer (stated in another comment), self-described, Sep 13, 2026. GPT-6 Astra after switching from GPT-5.6 Sol for coding.
- Unfavorable
gpt-6-astra 2.5x base in subscription
Comment on "Astra for Coding: Why Are We Doing This Again?". AmazingTurtle, Hacker News commenter, self-described, Sep 11, 2026. GPT-6 Astra in Codex on a subscription, rebasing and test-fixing tasks.
- Unfavorable
it'll use a lot of extra tokens in the process
Comment on "Pop!_OS bans AI-generated code from much of its codebase". williamcotton, Hacker News commenter, self-described, Oct 3, 2026. GPT-6 Astra High on a project built entirely with it.
- Favorable
ChatGPT usage (even 6 Astra Pro) is essentially unmetered on the 20x plan
Comment on "GPT-6 Sol and Luna". jeffnash, Hacker News commenter on Codex Pro 20x, self-described, Sep 22, 2026. GPT-6 Astra in Codex and ChatGPT on the Codex Pro 20x plan.
- Unfavorable
A token eating machine like no other
Comment on "GPT-6 Sol and Luna". jorl17, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra at High and Max.
- Favorable
With $20 for a one-month sub you can get a decent amount of GPT-6 Astra usage
Comment on "Don't be the out of touch Kung Fu master". heaney-555, Hacker News commenter, self-described, Sep 13, 2026. GPT-6 Astra on a $20 monthly subscription.
- Favorable
claude-opus-5.5 (max) uses 119k tokens per "intelligence index task" while gpt-6-astra (max) uses 27k
Comment on "Best LLM for every budget, updated daily". neuronexmachina, Hacker News commenter, self-described, Sep 24, 2026. GPT-6 Astra (max) token use on the Artificial Analysis index.
- Unfavorable
GPT-6 Astra made +$157k but cost $56
Comment on "Cafe Bench: Can LLMs run a coffee chain for a year?". zodwick, author of Cafe Bench at Dot (stated in the comment), self-described, Sep 23, 2026. GPT-6 Astra on Cafe Bench, a coffee-chain world simulation.
- Unfavorable
GPT-6 Astra burns my 5-hour credits in an hour or so
Comment on "Claude Opus 5.5". dexterlagan, Hacker News commenter on $20 OpenAI and Claude plans, self-described, Sep 27, 2026. GPT-6 Astra on a $20 ChatGPT subscription.
- Unfavorable
Astra is really fantastic but it's too expensive
Comment on "Ask HN: What default model do you use and why?". ewindisch, Hacker News commenter using 50 to 90B tokens a month, self-described, Sep 12, 2026. GPT-6 Astra as a default model candidate.
- Unfavorable
only with Astra and that is not financially viable
Comment on "What if AI worked at 1.000.000 tokens per seconds?". echohive42, Hacker News commenter, self-described, Oct 3, 2026. GPT-6 Astra on Codex ultrafast.
- Favorable
consistently catches more issues than Sol 5.6, using fewer tokens
Comment on "Everyone should slow down AI development except for me". sampullman, Hacker News commenter who runs a review bot, self-described, Sep 13, 2026. GPT-6 Astra medium effort in a code review bot.
- Unfavorable
Compared to Astra where I can watch the limit draining live
Comment on "Claude Code reads AGENTS.md only when telemetry is on [fixed]". user43928, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Astra High in the Codex app.
- Unfavorable
it burns through a giant percentage of my 5-hour allowance
Comment on "Plan mode is dead". robertlagrant, Hacker News commenter on the £20 subscription, self-described, Sep 26, 2026. GPT-6 Astra for homelab work on a £20 subscription.
- Unfavorable
Astra is usable for coding but slow and very expensive
Comment on "MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis". jmaker, Hacker News commenter on the $200 Codex Pro plan, self-described, Sep 22, 2026. GPT-6 Astra in Codex for coding and copy editing.
- Unfavorable
And too expensive to use
Comment on "GPT-6 Sol and Luna". cmrdporcupine, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra for planning and UI work.
- Unfavorable
Astra used 20x and Fable used 15x of what Sol did
Comment on "Why isn't the industry freaking out about DeepSeek 4.1 Flash?". Quothling, Hacker News commenter, self-described, Oct 8, 2026. GPT-6 Astra in Copilot cowork on one coding task, compared with Sol and Fable.
- Unfavorable
the rate limit is consumed far too quickly, making it nearly impossible to complete even minor tasks within a single session
GPT-6 Astra: Usage limits consuming rapidly / short session length. imtiyazali73, GitHub user on Plus filing on openai/codex, self-described, Sep 6, 2026. GPT-6 Astra in the Codex App on Plus.
- Unfavorable
my entire weekly Codex allowance was exhausted during a single ZITADEL staging upgrade and migration validation workflow
Severe weekly allowance regression: GPT-6 Astra High/Fast exhausts weekly quota in one day. mrak-, GitHub user on ChatGPT Prolite filing on openai/codex, self-described, Oct 19, 2026. GPT-6 Astra High in Fast mode in Codex Desktop.
- Unfavorable
you wait 10% usage and 1 hr for terrible response
GPT-6 Astra is so unreliable. lehoho248, building an AI media studio, Carnegie Mellon Engineering (stated in X bio), self-described, Oct 21, 2026. GPT-6 Astra on prompts for product work.
- Favorable
The limits are very generous. I've been working with it for about an hour and have used only 1% of my weekly limit
First impressions of GPT-6 Astra. Gegam245074, engineering manager (stated in X bio), self-described, Sep 4, 2026. GPT-6 Astra at xhigh for code review and coding.
Speed 41%
- Favorable
~80% cheaper and 30% faster in agentic coding
Comment on "An Alien Mind". gertlabs, account that runs Gert Labs multi-agent coding evaluations (stated in the comment), self-described, Sep 6, 2026. GPT-6 Astra in 100 multi-agent coding environments via the OpenAI Flex endpoint on OpenRouter.
- Unfavorable
astra ran for more than 6 hours and still wasn't done
Comment on "Astra for Coding: Why Are We Doing This Again?". AmazingTurtle, Hacker News commenter, self-described, Sep 11, 2026. GPT-6 Astra in Codex on a subscription, rebasing and test-fixing tasks.
- Unfavorable
Unbearably, annoyingly slow
Comment on "GPT-6 Sol and Luna". jorl17, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra at High and Max.
- Unfavorable
Incredibly slow (prompts running for 30/40 minutes) to do simple things
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". moshegramovsky, Hacker News commenter on a $200 OpenAI plan, self-described, Sep 29, 2026. GPT-6 Astra high thinking on a complex infra project across a large codebase.
- Unfavorable
although it was sluggish in comparison
Comment on "GPT-6 Astra". rafaelmn, Hacker News commenter, self-described, Sep 5, 2026. GPT-6 Astra on a technical problem compared with Gemini Flash 3.8.
- Favorable
It's also extremely fast
Comment on "Ask HN: What default model do you use and why?". asd88, Hacker News commenter with metered tokens at work, self-described, Sep 12, 2026. GPT-6 Astra at work after switching from Claude Opus and Fable.
- Favorable
Astra, which finished fastest, had a highscore of around 1.7Mm
Comment on "Analyzing Frontier Model Progress with My Favourite Game: Prince of Persia". criemen, Hacker News commenter, self-described, Sep 26, 2026. GPT-6 Astra hill-climbing an Asteroids client task.
- Favorable
using a basic harness to send commands to play and reads frames as images. Beats the game in real time
Comment on "Astra Plays Montezuma's Revenge [video]". telotortium, Hacker News commenter, self-described, Sep 9, 2026. GPT-6 Astra (low reasoning, fast mode) in codex-cli playing a game from frames.
- Favorable
with codex ultrafast we are near 500 TPS but only with Astra
Comment on "What if AI worked at 1.000.000 tokens per seconds?". echohive42, Hacker News commenter, self-described, Oct 3, 2026. GPT-6 Astra on Codex ultrafast.
- Unfavorable
It is way slower than 5.6 sol
Comment on "Ask HN: Initial Thoughts on GPT-6 Astra?". Alhaji123, Hacker News commenter in the Daybreak program (stated in the comment), self-described, Sep 6, 2026. GPT-6 Astra under Daybreak on reverse engineering.
- Unfavorable
Astra is state-of-the-art on most robotics benchmarks, but its too slow
Comment on "Astra as a Robotics World Model". quantbagel, Hacker News commenter who distilled Astra into a world model (stated in the comment), self-described, Oct 2, 2026. GPT-6 Astra on robotics benchmarks.
- Unfavorable
because Astra is slow at answering
Comment on "Ask HN: Initial Thoughts on GPT-6 Astra?". Topfi, Hacker News commenter who runs personal model evals (stated in comments), self-described, Sep 5, 2026. GPT-6 Astra (on Light) in the Codex app with voice and computer use.
- Unfavorable
I suspect Astra Max took so long because it's the big model and doing the most thinking
Comment on "Your computer is more powerful than you think". ben_w, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Astra Max in ChatGPT.
- Favorable
I can have Astra implement a small Rust change in 10 seconds
Comment on "GPT‑Live‑1 in the API". dist-epoch, Hacker News commenter, self-described, Sep 11, 2026. GPT-6 Astra on small Rust changes.
- Unfavorable
Astra is usable for coding but slow
Comment on "MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis". jmaker, Hacker News commenter on the $200 Codex Pro plan, self-described, Sep 22, 2026. GPT-6 Astra in Codex for coding and copy editing.
- Favorable
On xhigh it feels a lot faster than GPT-5.6 Sol
First impressions of GPT-6 Astra. Gegam245074, engineering manager (stated in X bio), self-described, Sep 4, 2026. GPT-6 Astra at xhigh for code review and coding.
- Unfavorable
I was using Astra XHigh on fast mode and only get 35 ish tokens per second which is insanely slow
Astra in fast mode is ~35 tokens/sec. EnvironmentalCow2947, r/codex poster, self-described, Oct 26, 2026. GPT-6 Astra XHigh on fast mode in Codex.
Reliability 14%
- Unfavorable
initially OpenRouter was giving Not Found errors for this model ID
Comment on "GPT-6 Astra on OpenRouter". XCSme, Hacker News commenter, self-described, Sep 4, 2026. GPT-6 Astra on OpenRouter.
- Unfavorable
I am just using GTP-6 Astra for some administrative prompts and it has been returning, "Error in message stream", for several minutes now
Comment on "Tell HN: Codex Is Down [fixed]". programmertote, Hacker News commenter, self-described, Sep 25, 2026. GPT-6 Astra for administrative prompts during a Codex outage.
- Unfavorable
I was wondering why GPT-6 astra has been performing so incredibly bad on codex for the last week
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". spwa4, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Astra on Codex.
- Unfavorable
Perhaps before Astra was nerfed. It is now the dumbest model right after Gemini
Comment on "Building a Linux GPU Driver for the M4 Mac Mini in One Month". varispeed, Hacker News commenter, self-described, Sep 15, 2026. GPT-6 Astra a few weeks after release.
- Unfavorable
Even Astra has been noticeably degraded for me and everyone else I have asked
Comment on "Ember-1". Gareth321, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Astra over several weeks of use.
- Unfavorable
since Astra released I found the model is somehow acting strange
Comment on "Claude Code reads AGENTS.md only when telemetry is on [fixed]". michaellee8, Hacker News commenter on the $200 plan, self-described, Sep 23, 2026. GPT-6 Astra and Sol on a $200 ChatGPT plan.
- Unfavorable
all models (Astra, Sol, Luna) hit rate limits all_the_time without me being anywhere close to the weekly limit
Comment on "MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis". loloisi, Hacker News commenter on the $200 plan, self-described, Sep 22, 2026. GPT-6 Astra, Sol and Luna in Codex.
- Favorable
It's never for very long, and I can switch to Astra
Comment on "GPT‑6 and Intelligent UI for everyone". wincy, Hacker News commenter on personal Pro and Codex enterprise accounts, self-described, Oct 7, 2026. GPT-6 Astra as a fallback when GPT-6.1 Sol is unavailable.
- Favorable
Astra seems to be getting anything but nerfed, given that its score is actually rising
Comment on "Livenerf: Has Opus 5.5 been nerfed yet?". jdthedisciple, Hacker News commenter, self-described, Sep 30, 2026. GPT-6 Astra on a public nerf tracker.
- Unfavorable
I hit limits (and the "we are disabling access to protect your data" warnings) all the time
Comment on "GPT-6 Sol and Luna". ChickeNES, Hacker News commenter on 20x ChatGPT and Claude plans, self-described, Sep 22, 2026. GPT-6 Astra Pro in ChatGPT on the 20x plan.
- Unfavorable
astra and sol 6.1 are often at capacity late at night during US hours
Comment on "Gemini 4 Argon". alex0015, Hacker News commenter and Codex user, self-described, Oct 13, 2026. GPT-6 Astra in Codex overnight.
- Unfavorable
Both the originally selected model and GPT-6 Astra fail with the same error
[Bug] All Codex projects report model capacity despite remaining Plus quota (GPT-6 Astra also fails). kklimt, GitHub user on Plus filing on openai/codex, self-described, Oct 22, 2026. GPT-6 Astra in Codex desktop on Windows, Plus.
- Unfavorable
GPT-6 Astra rejects every prompt as a potential usage-policy violation, including harmless prompts
[Windows] GPT-6 Astra rejects every prompt with "Invalid prompt". 1171995952, GitHub user on ChatGPT Pro filing on openai/codex, self-described, Sep 17, 2026. GPT-6 Astra in the Codex Windows app and codex exec.
- Unfavorable
However, the outputs consistently behave like GPT-5.6 Luna
Codex Desktop (Local): GPT-6 Astra selected, but outputs consistently behave like GPT-5.6 Luna. cq2562894828-svg, GitHub user on Pro 5x filing on openai/codex, self-described, Oct 26, 2026. GPT-6 Astra selected in Codex Desktop and Codex web.