Cost
$0.72per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at max effort.
GPT Sol model by OpenAI
GPT-6.1 Sol
OpenAI's newer Sol model, close to GPT-6 Astra on complex work at a lower cost. On OpenAI's own OSWorld 2.1 computer-use run (offline set) it scores 78%, 2.9 points under GPT-6 Astra at about a seventh of the cost per task. API model gpt-6.1-sol, with a 1,050,000-token context on the OpenAI API; Microsoft Foundry caps input at 922,000 tokens.
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.This model
- GPT LunaOpenAI's most efficient GPT model tier for focused, high-volume tasks.GPT-6 Luna
- GPT AstraOpenAI's highest-capability GPT model tier.GPT-6 Astra
- 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 Sol, version 6.1
- Released
- Sep 29, 2026 Current
- In its family
- The newest of 3 GPT Sol releases.
Strengths and weaknesses
Compare with other models Up to 3 beside GPT-6.1 Sol
- GPT-6.1 Sol
Suggested comparisons
The models a buyer weighs against GPT-6.1 Sol, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside GPT-6.1 Sol.
GPT-6.1 Sol
Among the 40 current releases on this chart, GPT-6.1 Sol ranks first of 28 on Math, first of 8 on Instruction following and third of 30 on Factuality. On Computer use, OpenAI's own figures on OSWorld 2.1 put GPT-6.1 Sol 2.9 points under GPT-6 Astra, 3.8 points above GPT-6.1 Terra and 22.5 points above GPT-6 Luna. It ranks lowest on Code, 26th of 37.
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-6.1 SolThis pageResults on 12 of 12 axes$2 / $10For prompts under 272K tokens; $4 / $15 at 272K or more, as OpenRouter lists it.81 tokens/sFirst token in 278 s
Prices and speeds read between Oct 26, 2026 and Oct 28, 2026.
GPT-6.1 Sol on each axis12 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-6.1 Sol55.1%
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-6.1 Sol54.2%
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-6.1 Sol93.7%
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-6.1 Sol95.4%
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-6.1 Sol52.9%
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-6.1 Sol64.9%
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. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- GPT-6.1 Sol78%reported by OpenAIBenchmark: OSWorld 2.1, score, offline set, v2.1 release, where the axis reads partial score, full 108-task set. From another source, so it is drawn and marked but not ranked with the others.OpenAI's own run at maximum reasoning effort, from the GPT-6.1 Terra launch chart, at $1.15 per task against $8.17 for GPT-6 Astra. OpenAI does not say whether it counts partial credit.
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-6.1 Sol83%
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-6.1 Sol86%
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-6.1 Sol61.8%Hallucination rate 51.9% 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-6.1 Sol69.5%SpeechMap tested it through OpenRouter at medium reasoning and counted 21.7% of requests denied and 8.8% 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-6.1 Sol82%On Oct 28, 2026, Scale AI ranked it 1st.Plus or minus 4.16 points (95% interval)
Cost, speed, capacity, quality and accuracy for GPT-6.1 Sol, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
73tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 284 s
- Whole answer
- 291 s
Capacity
1.05Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 128K
- Reads
- Text, Images
Quality
51.8of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,608 Elo
- Terminal-Bench 4.0
- 56.1%
- Epoch Capabilities Index
- 168
Hallucination
51.9%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
- 61.8%
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-6.1 Sol: Cached input.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | GPT-6.1 Sol | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness | 55.1% | GPT-6.1 SolEffort: not published. Harness: mini-swe-agent. | Vals.ai | Oct 24, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 54.2% | GPT-6.1 Sol (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 | Sep 29, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 95.4% | Effort: max. Harness: none. | Epoch AI | Sep 29, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 52.9% | GPT-6.1 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | 64.9% | GPT-6.1 Sol (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness. | Artificial Analysis | Oct 28, 2026 |
| Computer use | OSWorld 2.1Score, offline set, v2.1 release. OpenAI's own run at maximum reasoning effort, from the GPT-6.1 Terra launch chart, at $1.15 per task against $8.17 for GPT-6 Astra. OpenAI does not say whether it counts partial credit.Stands in for OSWorld 2.1, partial score, full 108-task set, v2.1 release, which has no run of GPT-6.1 Sol yet. | 78% | GPT-6.1 Sol (Max)Effort: max. Harness: OpenAI computer-use harness.Not drawn: OpenAI 71.4% in its maker's own harness, Sep 29, 2026. Source | OpenAIReported by OpenAI | Oct 26, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 83% | GPT-6.1 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 86% | GPT-6.1 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 61.8%Hallucination rate 51.9% in the same run (lower is better) | GPT-6.1 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. SpeechMap tested it through OpenRouter at medium reasoning and counted 21.7% of requests denied and 8.8% evaded. | 69.5%0.1% of requests failed at the provider and count against it | Effort: medium. Harness: none. | SpeechMap.AI | Oct 27, 2026 |
| Instruction following | MultiChallengeAccuracy, Scale AI run. On Oct 28, 2026, Scale AI ranked it 1st. | 82%Plus or minus 4.16 points (95% interval) | gpt 6.1 SolEffort: not published. Harness: none. | Scale AI SEAL | Oct 28, 2026 |
Price and speed
- GPT-6.1 Sol lists at $2 per million input tokens and $10 per million output tokens. For prompts under 272K tokens; $4 / $15 at 272K or more, as OpenRouter lists it. OpenAI pricing, Oct 26, 2026.
- GPT-6.1 Sol, at max effort, writes 81.1 output tokens per second on OpenAI's API, and its first token arrives 278 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-6.1 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-6.1 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 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-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-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 |
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| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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-6.1 Sol93.7%
- GPT-6 Astra93.7%
- 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-6.1 Sol 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-6.1 Sol | 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 27, 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 27, 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. | 12,938 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task. | $0.12 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task. | $0.18 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task. | $0.34 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task. | $0.38 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task. | $0.25 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per taskLower is better. What one Intelligence Index task cost AA at list price, input, cache, output and reasoning tokens together. | $0.72 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | $1,082 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Output tokens per taskLower is better. Tokens the model wrote per Intelligence Index task, reasoning included: how verbose it is. | 38,128 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 25,190 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Speed | ||||
| End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt. | 368 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 291 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Time to first answer token, 100K promptLower is better. Median seconds to the first answer token with a 100,000-token prompt. | 358 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Time to first answer tokenLower is better. Seconds until the first answer token, after any reasoning, on AA's API runs. | 284 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long. | 52 tokens/s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Output speedMedian output tokens per second on AA's API runs, with the 5th and 95th percentile when AA prints them. | 73 tokens/s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | 527 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | 358 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | 284 s | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | 51.9% | Max effort | Artificial Analysis | Oct 28, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 61.8% | Max effort | Artificial Analysis | Oct 28, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 41.5 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | 73.9% | Max effort | Epoch AI | Sep 29, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,555 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows. | 50% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it. | 60% | Max effort | Mercor (via Epoch AI) | Oct 26, 2026 |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 31% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval. | 1,608 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| MLCR (AA run)AA's MLCR overall score for long, multi-document reading. | 38.3% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 83% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it. | 2,744 | 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. | 94.2% | Max effort | ARC Prize Foundation (via Epoch AI) | Oct 26, 2026 |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 68% | 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-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 96.5% | Max 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. | 168 | GPT-6.1 Sol | Epoch AI | Oct 26, 2026 |
| FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks. | 49.1% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run. | 100% | Max effort | Epoch AI | Sep 29, 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 | Sep 29, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 95.4% | Max effort | Epoch AI | Sep 29, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 52.9% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 51.8 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 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. | 62.8 | Max effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 86.0% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run. | 80% | Max effort | Epoch AI | Sep 29, 2026 |
| OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run. | 100% | Max effort | Epoch AI | Sep 29, 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. | 54.2% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness. | 56.1% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness. | 58.1% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| WebDev ArenaWebDev Arena score from human pairwise votes on web builds, with its 95% interval, as Epoch AI republishes it. | 1,759 | Max effort | LMArena (via Epoch AI) | Oct 26, 2026 |
| WeirdML v3, best runWeirdML v3 maximum performance across runs, as Epoch AI republishes it. | 50.6% | Extra-high effort | Håvard Tveit Ihle (via Epoch AI) | Oct 26, 2026 |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 59.3 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 53.9 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 54 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points. | 51.8 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 57.7 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 57 | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Harvey Legal Lab (AA run)AA's run of Harvey's legal task lab. | 6.9% | GPT-6.1 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
Routes, prices and uptime
Where GPT-6.1 Sol 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-6.1 Sol 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-6.1-sol | us./global. profiles on bedrock-runtime; bedrock-mantle us-east-1; 1M context, 131,072 output; EOL date not announced; tiers: Standard, Ultrafast at 6x (Priority, Flex, Reserved not supported) | Amazon Web Services, Models at a glanceAmazon Web Services, GPT-6.1 Sol |
| Codex | Available | gpt-6.1-sol | codex -m gpt-6.1-sol; Codex CLI and IDE extension | OpenAI, Models |
| Databricks | Available | system.ai.gpt-6-1-sol | Databricks' supported-models page, read Oct 30, 2026, lists GPT-6.1 Sol as system.ai.gpt-6-1-sol, pay-per-token, for use through the Responses API; it is not supported in AI Playground. The foundation-model overview page, read Oct 30, 2026, lists GPT-6 Astra and GPT-5.6 Sol, Terra and Luna among OpenAI models, and not GPT-6.1 Sol. | Databricks, Databricks-hosted inferenceDatabricks, Detailed list of models supported by Databricks Foundation Model APIs |
| The maker's own API | Available | gpt-6.1-sol | 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-6.1 Sol ModelOpenAI, GPT-6 Luna Model |
| GitHub Copilot | Available | not statedpicker label GPT-6.1 Sol | available (GA); missing from per-client table | GitHub |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub, GitHub Models |
| Microsoft Foundry | Available | gpt-6.1-sol | 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-6.1-sol | OpenCode Zen, OpenAI Responses endpoint | Anomaly (OpenCode), ModelsOpenCode (Anomaly) |
| OpenRouter | Available | openai/gpt-6.1-sol | 1,050,000 / 128,000; batch variant listed | OpenRouter |
| Snowflake Cortex | Preview | openai-gpt-6.1-sol | Private preview | Snowflake |
| Windsurf / Devin | Available | gpt-6-1-sol-highgpt-6-1-sol-high-prioritygpt-6-1-sol-lowgpt-6-1-sol-low-prioritygpt-6-1-sol-maxgpt-6-1-sol-max-prioritygpt-6-1-sol-mediumgpt-6-1-sol-medium-prioritygpt-6-1-sol-xhighgpt-6-1-sol-xhigh-priority | Low to Max thinking, plus Fast (priority) variants | Cognition (Devin, formerly Windsurf), AI Models |
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 $2 / $10 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 | $2 / $10 | OpenAI, Oct 26, 2026 | ||
| Artificial Analysis price record | $2 / $10 | $0.1 | Blended $4, 3 input : 1 output, no cacheBlended $1.47, 7 cache-hit : 2 input : 1 outputCache write $2.50 | Artificial Analysis, Oct 27, 2026 |
| OpenRouterprompts under 272K tokens | $2 / $10 | $0.1 | Cache read $0.2, prompts of 272K tokens or moreCache write $5, 5-minute cache, prompts of 272K tokens or moreCache write $2.50, 5-minute cache, prompts under 272K tokensLong context $4 / $15, prompts of 272K tokens or more | OpenRouter, Oct 28, 2026 |
| Through OpenRouter, 8 provider endpoints. OpenRouter, Oct 28, 2026 | ||||
| Azureprompts under 272K tokens | $2 / $10 | $0.1 | Cache read $0.2, prompts of 272K tokens or moreCache write $5, 5-minute cache, prompts of 272K tokens or moreCache write $2.50, 5-minute cache, prompts under 272K tokensLong context $4 / $15, prompts of 272K tokens or more | Up 76.5% / 0%1.05M context, 128K output |
| OpenAIprompts under 272K tokens | $2 / $10 | $0.1 | Cache read $0.2, prompts of 272K tokens or moreCache write $5, 5-minute cache, prompts of 272K tokens or moreCache write $2.50, 5-minute cache, prompts under 272K tokensLong context $4 / $15, prompts of 272K tokens or more | Up 100% / 100%1.05M context, 128K output |
| Amazon Bedrock (us-east-1)prompts under 272K tokens | $2.20 / $11 | $0.11 | Cache read $0.22, prompts of 272K tokens or moreCache write $5.50, 5-minute cache, prompts of 272K tokens or moreCache write $2.75, 5-minute cache, prompts under 272K tokensLong context $4.40 / $16.50, prompts of 272K tokens or more | Up 100%1.05M context, 128K output |
| Azure (eu)prompts under 272K tokens | $2.20 / $11 | $0.11 | Cache read $0.22, prompts of 272K tokens or moreCache write $5.50, 5-minute cache, prompts of 272K tokens or moreCache write $2.75, 5-minute cache, prompts under 272K tokensLong context $4.40 / $16.50, prompts of 272K tokens or more | Up 99.9% / 100%1.05M context, 128K output |
| Azure (us)prompts under 272K tokens | $2.20 / $11 | $0.11 | Cache read $0.22, prompts of 272K tokens or moreCache write $5.50, 5-minute cache, prompts of 272K tokens or moreCache write $2.75, 5-minute cache, prompts under 272K tokensLong context $4.40 / $16.50, prompts of 272K tokens or more | Up 99.9% / 100%1.05M context, 128K output |
| OpenAI (ultrafast)prompts under 272K tokens | $12 / $60 | $0.6 | Cache read $1.20, prompts of 272K tokens or moreCache write $30, 5-minute cache, prompts of 272K tokens or moreCache write $15, 5-minute cache, prompts under 272K tokensLong context $24 / $90, prompts of 272K tokens or more | Up 100%1.05M context, 128K output |
| OpenAI (fast, priority) | Cache read $0.4, priority tier, prompts of 272K tokens or moreCache read $0.2, priority tier, prompts under 272K tokensCache write $10, priority tier, 5-minute cache, prompts of 272K tokens or moreCache write $5, priority tier, 5-minute cache, prompts under 272K tokensLong context $8 / $30, priority tier, prompts of 272K tokens or morePriority $4 / $20, priority tier, prompts under 272K tokens | Up 100% / 100%1.05M context, 128K output | ||
| OpenAI (flex) | Cache read $0.1, flex tier, prompts of 272K tokens or moreCache read $0.05, flex tier, prompts under 272K tokensCache write $2.50, flex tier, 5-minute cache, prompts of 272K tokens or moreCache write $1.25, flex tier, 5-minute cache, prompts under 272K tokensFlex $1 / $5, flex tier, prompts under 272K tokensLong context $2 / $7.50, flex tier, prompts of 272K tokens or more | Up 67.3% / 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: Microsoft Azure | 60 tokens/s | 201 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: OpenAI (Fast) | 140 tokens/s | 150 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: OpenAI (Flex) | 117 tokens/s | 214 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: OpenAI (Ultrafast) | 333 tokens/s | 57 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: OpenAI | 81 tokens/s | 278 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-6.1 Sol 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
- 5.6Current. In 5 products we coverPrice$4 / $20Speed101.9 tok/s
- 6Legacy. In 5 products we coverPrice$2 / $10Speed111.7 tok/s
- This page6.1Current. In 6 products we coverPrice$2 / $10Speed81.1 tok/s
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
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-6.1 Sol can power. A product supplies the rest.
Product & Engineering, Software Development
Agentic Software Development
- Primary role
- Foundation Model / Reasoning Engine
GPT-6.1 Sol 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-6.1 Sol 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. In ChatGPT it runs only in Work and Codex, and is also on Business, Enterprise and Edu plans.
- CodexPlus, Pro, Business, Enterprise, Edu
- 15-160 local messages per five-hour period on Plus and Standard Business (estimate); Pro plans currently have no five-hour limit; available only in Work and Codex; off by default for Enterprise and Edu until an administrator enables it
- PerplexityPro, Max
- In Perplexity's Search model picker on Pro and Max; 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-6.1 Sol, then those of the clouds and APIs that serve it.
- AI SDK vs OpenAI Agents SDK: Any Model or OpenAI's Agent Loop?Names GPT-6.1 Sol
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Names GPT-6.1 Sol
- Claude Code vs Codex: Which Agentic Coding Workflow Fits Your Team?Names GPT-6.1 Sol
- Codex vs Devin: Which Delegated Coding Agent Fits Your Team?Names GPT-6.1 Sol
- Codex vs GitHub Copilot: ChatGPT-Bundled Agent or GitHub-Native Platform?Names GPT-6.1 Sol
- Cursor vs Codex: Own Editor or ChatGPT-Bundled Agent?Names GPT-6.1 Sol
- Factory vs Codex: Every Model Under One Plan, or OpenAI's Agent Inside ChatGPT?Names GPT-6.1 Sol
- Jules vs Codex: Google AI Plan or ChatGPT Plan for Delegated Coding?Names GPT-6.1 Sol
- Open WebUI vs ChatGPT: Self-Host the Assistant or Buy Seats?Names GPT-6.1 Sol
- Open WebUI vs Claude: Self-Hosted Chat or Claude Team and Enterprise?Names GPT-6.1 Sol
- OpenAI API vs Azure OpenAI: Same Models, Different ContractsNames GPT-6.1 Sol
- OpenAI API vs Gemini API: Who Finishes the Task for Less?Names GPT-6.1 Sol
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Names GPT-6.1 Sol
- Amazon Bedrock vs Claude API: Buying Claude Through AWS or From AnthropicCompares routes that serve GPT-6.1 Sol
- Amazon Bedrock vs Microsoft Foundry: Which Cloud AI Platform Fits Your Stack?Compares routes that serve GPT-6.1 Sol
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve GPT-6.1 Sol
- Gemini API vs Amazon Bedrock: One Model Family or a Model Marketplace?Compares routes that serve GPT-6.1 Sol
- Gemini Enterprise Agent Platform vs Microsoft Foundry: Google Cloud or Azure for Models and AgentsCompares routes that serve GPT-6.1 Sol
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve GPT-6.1 Sol
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve GPT-6.1 Sol
What practitioners report
Strongest on Cost, weakest on Reliability.
Each figure is the share of accounts naming GPT-6.1 Sol 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. | 55% | 12 favorable, 10 not, 22 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 40% | 4 favorable, 6 not, 10 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | 38% | 3 favorable, 5 not, 8 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | 27% | 3 favorable, 8 not, 11 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 74% | 14 favorable, 5 not, 19 authors |
| SpeedResponse time, time to first token, and throughput. | 37% | 7 favorable, 12 not, 19 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 13% | 1 favorable, 7 not, 8 authors |
Every model on these seven axes
| Axis | GPT-6.1 Sol | GPT-6.1 Terra | GPT-6 Luna | GPT-6 Astra | 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 | 55%12 favorable, 10 not, 22 authors | 33%3 favorable, 6 not, 8 authors | 55%16 favorable, 13 not, 29 authors | 44%12 favorable, 15 not, 26 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 | 40%4 favorable, 6 not, 10 authors | 40%2 favorable, 3 not, 5 authors | 33%3 favorable, 6 not, 9 authors | 62%8 favorable, 5 not, 13 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 | 38%3 favorable, 5 not, 8 authors | Only concerns on record0 favorable, 1 not, 1 author | 20%1 favorable, 4 not, 5 authors | 27%3 favorable, 8 not, 11 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 | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 2 not, 2 authors | 25%2 favorable, 6 not, 8 authors | 41%7 favorable, 10 not, 17 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 | 74%14 favorable, 5 not, 19 authors | 80%8 favorable, 2 not, 9 authors | 79%22 favorable, 6 not, 26 authors | 29%7 favorable, 17 not, 23 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 | 37%7 favorable, 12 not, 19 authors | 83%5 favorable, 1 not, 5 authors | 45%5 favorable, 6 not, 11 authors | 41%7 favorable, 10 not, 17 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 | 13%1 favorable, 7 not, 8 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 5 not, 5 authors | 14%2 favorable, 12 not, 14 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 75 accounts behind GPT-6.1 Sol's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis and the web for accounts that name GPT-6.1 Sol.
Quality and reasoning 55%
- Favorable
I'd rank Sol 6.1 only slightly behind Opus 5.5 in intelligence and both significantly ahead of anything else I've used
Comment on "DeepSeek-v4.1-Flash-1017". ac29, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") against Opus 5.5 in daily use.
- Favorable
it took ~4x longer in a review, found less and planned worse than GPT 6.1 Sol
Comment on "DeepSeek-v4.1-Flash-1017". AmazingTurtle, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol reviewing a 200-file C++ game engine change, against DeepSeek v4.1 Flash, GLM 5.3 Flash and GPT-5.6 Sol.
- Unfavorable
Overall, opus executes a bit better than 6.1 sol
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". Jacob Miller (jjcm), working on diffui.ai, formerly Figma (stated in HN profile), self-described, Sep 29, 2026. GPT-6.1 Sol on an image-to-HTML flow against Opus 5.5.
- Favorable
GPT-6.1 Sol got all answers correct
Comment on "Claude Haiku 5.5". Chris Parmer, Co-Founder and CPO of Plotly, Oct 7, 2026. GPT-6.1 Sol on the Plotly DataAnalyticsBench, 40 data analytics questions.
- Favorable
6.1-Sol is noticeably better at most tasks I throw at it
Comment on "Muse Spark Open". mapkkk, Hacker News commenter, self-described, Oct 15, 2026. GPT-6.1 Sol at medium effort with Hermes agent, against GLM 5.3 Flash high.
- 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, AI evaluations company (stated in HN profile, gertlabs.com), self-described, Sep 30, 2026. GPT-6.1 Sol across 100 unsaturated coding and engineering environments through the API.
- Favorable
it all did all of it very well
Comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". super256, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (the author writes "6.1-Sol") adding Windows support to an open source project.
- Unfavorable
GPT 6.1 Sol misses this and code fails at runtime
Comment on "Mistral Large 4". CharlieDigital, Hacker News commenter (works at a series-C startup, stated in HN profile), self-described, Oct 6, 2026. GPT-6.1 Sol updating an API backend for new models.
- 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, self-described, Oct 16, 2026. GPT-6.1 Sol building bots for a ModernUO server, against Opus 5.5.
- Unfavorable
6.1 sol was atrain wreck in my project leaving dead boddies everywhere
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". jp_gorman, Hacker News commenter, self-described, Oct 1, 2026. GPT-6.1 Sol against GPT-5.6 Sol on the author's project.
- Favorable
is 100x or so better at reverse engineering and coding
Comment on "500B tokens later: Letting AI agents decompile a first-person shooter". aetherspawn, Hacker News commenter, self-described, Oct 11, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") on a long reverse-engineering task, against Sonnet.
- Favorable
highly intelligent and extremely token-efficient
Comment on "Samsung TV privacy issues". nekitamo, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (listed as "GPT Sol Latest (Sol 6.1)") in Claude Code on a crackme reverse-engineering benchmark.
- Unfavorable
Sol 6.1 will just happily grind on permutations of a base shape spelling that M2C outputs
Comment on "Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto line". potsandpans, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (the author writes "sol 6.1") decompiling a PlayStation game, against Opus and Astra.
- Unfavorable
schema transitions aren't needed pre-release (still a case with GPT-6.1 Sol
Comment on "Port of the TypeScript compiler, checker and lsp to Rust, by LLM". Topfi, Hacker News commenter, self-described, Oct 8, 2026. GPT-6.1 Sol on patches to Firefox source code.
- Favorable
6.1 Sol is very good at synthesizing actual information it finds without hallucinating
Comment on "The gap in shared understanding of LLM capability is widening". satvikpendem, Hacker News commenter, self-described, Oct 12, 2026. GPT-6.1 Sol (the author writes "6.1 Sol") in ChatGPT for research.
- Favorable
Sol 6.1 would have long ported it correctly more thoroughly
Comment on "DeepSeek V4.1 Flash 1017 (Max)". harrygeez, Hacker News commenter, self-described, Oct 19, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") porting old games, against DeepSeek 4.1.
- Unfavorable
Hallucinates over the simplest things
My observations on GPT-6.1 Sol so far. Mari (Tech_girl), developer and technical writer (stated in X bio), self-described, Oct 25, 2026. GPT-6.1 Sol.
- Unfavorable
Feels so much dumb...
GPT 6.1 Sol in last couple of hours is not usable. Dawid Skinder, designer and manager who leads creative and dev teams in Web3 and fintech (stated in X bio), self-described, Oct 25, 2026. GPT 6.1 Sol.
- Unfavorable
It created one table with ONE column and ONE row and put the ENTIRE JSON IN ONE CELL
GPT-6.1 Sol put the entire JSON in one cell. necropheus, computer scientist (stated in X bio), self-described, Oct 25, 2026. GPT-6.1 Sol migrating an internal tasks app from JSON to SQL.
- Favorable
GPT-6.1 Sol has been flawless throughout the execution phase
Rewriting a backend in Rust with GPT-6.1 Sol. ____NanaKong, operator focused on AI and IT infrastructure (stated in X bio), self-described, Oct 23, 2026. GPT-6.1 Sol rewriting a Python backend in Rust, with GPT-6 Astra for documentation.
- Favorable
It's just more consistent at one-shotting and staying inside the instruction boundary.
GPT-6 Astra Max still feels less reliable than 6.1 Sol Max. Mike (mikechaves_io), creative director and creative technologist (stated in X bio), self-described, Oct 20, 2026. GPT-6.1 Sol Max (the author writes "6.1 Sol Max") against GPT-6 Astra Max for coding.
- Unfavorable
6.1-sol is like elementary compared to opus-5.5
6.1-sol is like elementary compared to opus-5.5. leoohoho (lehoho248), building an AI media studio, Carnegie Mellon engineering (stated in X bio), self-described, Oct 21, 2026. GPT-6.1 Sol (the author writes "6.1-sol") against Opus 5.5.
Tool use and structured output 40%
- Favorable
Other models like 6.1 Sol only made 18 for that question
Comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". Chris Parmer, Co-Founder and CPO of Plotly, Oct 24, 2026. GPT-6.1 Sol on the Plotly data analytics benchmark, against Kimi K3.1 Pro.
- Favorable
Sol thinks less and is much smarter about the commands it runs, resulting in far fewer turns to get the same thing done
Comment on "DeepInfer: High-performance inference framework for DeepSeek models". RussianCow, runs a software consultancy (stated in HN profile), self-described, Oct 20, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") on agentic tasks, against DeepSeek V4.1 Flash.
- Favorable
it did it with zero supervision and a single /goal
Comment on "500B tokens later: Letting AI agents decompile a first-person shooter". aetherspawn, Hacker News commenter, self-described, Oct 11, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") on a long reverse-engineering task, against Sonnet.
- Unfavorable
The more it uses it, the worse it gets at giving prompts to subagents
Comment on "What is Codemode". Starlevel004, Hacker News commenter, self-described, Oct 7, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") with code mode and subagents.
- Unfavorable
Especially when giving it goals it will happily run in dumb circles just burning tokens without any real work
Comment on "Gemini 4 Argon". Macuyiko, Hacker News commenter, self-described, Oct 13, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") given goals.
- Unfavorable
More like near-miss on JSON schema output
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". thimble_io, Hacker News commenter, self-described, Sep 30, 2026. GPT-6.1 Sol, in the launch thread.
- Unfavorable
often uses the `find` tool incorrectly. I think its choosing the wrong tool.
GPT-6.1 Sol uses
findfor exact-symbol lookups. asmartin-ai, oh-my-pi user (GitHub issue author), self-described, Oct 25, 2026. openai-codex/gpt-6.1-sol as main model in oh-my-pi 18.12.6 through a ChatGPT Plus/Pro Codex subscription. - Unfavorable
Sol at xhigh spent 42m48s on the interrupted review turn without completing that exchange
GPT-6.1 Sol xhigh repeatedly restarts Claude review jobs and introduces output-cap failures. shikyo13, Codex Desktop user (GitHub issue author), self-described, Oct 24, 2026. gpt-6.1-sol at xhigh in Codex Desktop 26.1021 orchestrating a Claude Opus 5.5 reviewer.
- Unfavorable
sending a message that causes Chat to invoke a tool fails with HTTP 400
OpenAI GPT-6.1-Sol tool calls fail in Chat with reasoning enabled. luizdodero, heym contributor (GitHub issue author), self-described, Oct 22, 2026. gpt-6.1-sol through a native OpenAI API credential on Chat Completions with function tools.
- Favorable
two successful tools including shell and external memory recall, with zero tool failures
VPS1: GPT 6.1 Sol through Codex OAuth verified on ten agents. ZedBiz44, operator of an OpenClaw agent deployment (GitHub issue author), self-described, Oct 3, 2026. GPT 6.1 Sol through Codex OAuth on ten OpenClaw agents.
Long context 38%
- Favorable
at 480,000, every run on both answered
How StackAI by Asana used Astra, Codex and Command to Reduce Browser Agent Costs. StackAI by Asana engineering blog, with Frank Hidalgo, CTO of StackAI, self-described, Oct 8, 2026. GPT-6.1 Sol running the StackAI by Asana browser agent across a 144-run caching and history study.
- Favorable
But it also works fine with GPT 6.1 Sol
Comment on "Mistral Large 4". Slartie, Hacker News commenter, self-described, Oct 6, 2026. GPT-6.1 Sol with a 1M context window on a multi-microservice workspace.
- Favorable
I don't notice much of a difference between Sol 6.1 1M and Opus 5.5 1M
Comment on "DeepSeek-v4.1-Flash-1017". cjbgkagh, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol (the author writes "Sol 6.1 1M") with the 1M context window, 10 to 16 parallel agents.
- Unfavorable
Sol 6.1 has a gold-fish memory
Comment on "DeepSeek-v4.1-Flash-1017". cromka, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") against Opus 5.5.
- Unfavorable
I'm running into this in the first 10% of the context window instead of waiting for it to get to 50%
GPT-6.1 Sol experiences context freeze far quicker than 5.6 Sol. Arlen22, VS Code user (GitHub issue author), self-described, Oct 21, 2026. GPT-6.1 Sol in VS Code 1.142 chat, against GPT-5.6 Sol.
- Unfavorable
When using GPT 6.1 sol, it appears unable to compress the context properly
GPT 6.1 Sol bug. steven961302-alt, Codex CLI user on a Pro plan (GitHub issue author), self-described, Oct 13, 2026. gpt 6.1 sol in Codex CLI 0.162.1 on macOS.
- Unfavorable
Codex interrupted real work for over five minutes to compact a session whose last reported usage was 193,193 tokens
Repeated early compaction across GPT-6.1 Sol and Astra: internal token counts exceed reported usage. future3OOO, Codex CLI user (GitHub issue author), self-described, Oct 1, 2026. gpt-6.1-sol at high reasoning effort in Codex CLI 0.159.2 with ChatGPT sign-in.
- Unfavorable
Loses context way too easily
My observations on GPT-6.1 Sol so far. Mari (Tech_girl), developer and technical writer (stated in X bio), self-described, Oct 25, 2026. GPT-6.1 Sol.
Developer experience 27%
- Favorable
Codex running 6.1-sol explains things so much more clearly that I don't feel I need to assert a style guide on its output
Comment on "GPT‑6 and Intelligent UI for everyone". PokeyCat, Hacker News commenter, self-described, Oct 8, 2026. GPT-6.1 Sol in Codex writing documentation.
- Favorable
6.1 sol on medium is quite good at getting things right the first time without overthinking and i prefer it over xhigh or max usually
Comment on "DeepSeek V4.1 Flash 1017 (Max)". slopinthebag, Hacker News commenter, self-described, Oct 19, 2026. GPT-6.1 Sol at medium reasoning effort.
- Unfavorable
6.1-sol invariably fails to do so unless I explicitly tell it that it's ok to run the tests
Comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". jaggederest, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (the author writes "6.1-sol") with an AGENTS.md that permits remote CI and PRs.
- Unfavorable
IT AUTOMATICALLY OPENED A PR ON BEHALF OF ME WITHOUT ME ASKING FOR EXPLICIT PERMISSION
Comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". super256, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (the author writes "6.1-Sol") adding Windows support to an open source project.
- Unfavorable
it decided to make some optimizations that I had not asked for on step E
Comment on "OpenAI Withdraws 3 Math Papers". CrazyStat, Hacker News commenter, self-described, Oct 8, 2026. GPT-6.1 Sol High in Codex on a six-step data pipeline.
- Favorable
If you dial it to normal/high/xhigh, Sol 6.1 is only a couple of minutes behind Astra
Comment on "Show HN: Open-source model routing for coding agents at Astra-level performance". waximabbax, Hacker News commenter, self-described, Oct 2, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") at max against normal, high and xhigh effort.
- Unfavorable
This makes GPT-6.1 Sol hit context compaction very quickly during normal coding work.
[Codex Desktop] GPT-6.1 Sol starts fresh threads at ~208k/258k context while GPT-6 Sol/Astra start at ~40k. LeonL1111, Codex Desktop user (GitHub issue author), self-described, Sep 30, 2026. GPT-6.1 Sol in Codex Desktop, against GPT-6 Sol and GPT-6 Astra on the same project.
- Unfavorable
while also expanding narrowly scoped requests into unrequested work
[Regression] GPT-6.1 Sol: 11-minute trivial Git cleanup and unrequested scope expansion. mhanayama, Codex user (GitHub issue author), self-described, Oct 23, 2026. GPT-6.1 Sol as a Codex coding agent.
- Unfavorable
Chat fails when using the OpenAI model `gpt-6.1-sol`.
[Bug]: GPT-6.1 Sol chat fails with reasoning/tool incompatibility and unsupported 'seed' argument. edwinjosechittilappilly, OpenRAG contributor (GitHub issue author), self-described, Oct 22, 2026. gpt-6.1-sol as the OpenAI chat model in OpenRAG.
- Unfavorable
Subscription authentication succeeds, but the onboarding hello probe fails
OpenAI subscription onboarding fails with gpt-6.1-sol and older Codex CLI. yelloduxx, Paperclip user (GitHub issue author), self-described, Oct 3, 2026. gpt-6.1-sol through a ChatGPT subscription in Paperclip with Codex CLI 0.156.1 to 0.160.0.
- Unfavorable
he confirmed gpt-6.1-sol-900k was resolving to 500000
gpt-6.1-sol-900k was resolving to 500000. Kaan (altemore), X user, self-described, Oct 25, 2026. GPT-6.1 Sol with the 900k context option (gpt-6.1-sol-900k) selected through a gateway.
Cost 74%
- Favorable
On GPT-6.1 Sol, the same agent cost 76x less and ran 5x faster, reading 89% of its input from cache.
How StackAI by Asana used Astra, Codex and Command to Reduce Browser Agent Costs. StackAI by Asana engineering blog, with Frank Hidalgo, CTO of StackAI, self-described, Oct 8, 2026. GPT-6.1 Sol running the StackAI by Asana browser agent across a 144-run caching and history study.
- Favorable
was quite cheap to run
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". Jacob Miller (jjcm), working on diffui.ai, formerly Figma (stated in HN profile), self-described, Sep 29, 2026. GPT-6.1 Sol on an image-to-HTML flow against Opus 5.5.
- Favorable
Sol is almost as good and way cheaper
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". thefourthchime, Hacker News commenter, self-described, Sep 29, 2026. GPT-6.1 Sol on a Pac-Man build bake-off against Opus 5.5 and GPT-6 Astra.
- Favorable
a median run cost me $0.52 vs $0.18 for Sonnet and $0.09 for Sol
Comment on "Gemini 4 Argon". ariwilson, Hacker News commenter, self-described, Oct 13, 2026. GPT-6.1 Sol through pi and OpenRouter on 11 bug fixes from the author's own projects.
- Favorable
Somehow GPT 6.1 Sol (medium) is cheaper per task ($0.21 vs $0.26)
Comment on "DeepSeek V4.1 Flash 1017 (Max)". Tiberium, Hacker News commenter, self-described, Oct 19, 2026. GPT-6.1 Sol (medium) against DeepSeek v4.1 Flash 1017 (max) on Artificial Analysis per-task figures.
- Favorable
the same result GPT-6.1-Sol accomplishes in, comparatively, two drops of thinking tokens
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". AspireOne, Hacker News commenter, self-described, Sep 29, 2026. GPT-6.1 Sol (medium) against DeepSeek v4.1 Flash on Artificial Analysis per-task figures.
- Unfavorable
but was 10x more expensive
Comment on "Claude Haiku 5.5". Chris Parmer, Co-Founder and CPO of Plotly, Oct 7, 2026. GPT-6.1 Sol on the Plotly DataAnalyticsBench, 40 data analytics questions.
- Unfavorable
GPT 6.1 Sol is ~6-7x more expensive for similar intelligence
Comment on "DeepSeek-v4.1-Flash-1017". TheArcane, Hacker News commenter, self-described, Oct 18, 2026. GPT-6.1 Sol against DeepSeek v4.1 Flash.
- Unfavorable
I have not been able to match usage costs to what I've been getting with glm 5.3 flash high
Comment on "Muse Spark Open". mapkkk, Hacker News commenter, self-described, Oct 15, 2026. GPT-6.1 Sol at medium effort with Hermes agent, against GLM 5.3 Flash high.
- Unfavorable
literally one prompt to do some code analysis, it didn't even complete it. And that was 6.1 sol xhigh
Comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". epolanski, Hacker News commenter, self-described, Oct 23, 2026. GPT-6.1 Sol at xhigh on the OpenAI $20 plan.
- Favorable
DeepSeek 4.1 Flash uses 10× more tokens than GPT-6.1 Sol for an equivalent task and delivers a lower-quality result
Comment on "Why isn't the industry freaking out about DeepSeek 4.1 Flash?". xzjis, Hacker News commenter, self-described, Oct 9, 2026. GPT-6.1 Sol against DeepSeek 4.1 Flash on tokens per task.
- Favorable
6.1-Sol is also cheaper than Sonnet 5.5 and much smarter
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". gertlabs, AI evaluations company (stated in HN profile, gertlabs.com), self-described, Sep 30, 2026. GPT-6.1 Sol across 100 unsaturated coding and engineering environments through the API.
- Favorable
sol 6.1 is both cheap and capable. i've been using it exclusively, i don't need to care about usage
Comment on "DeepSeek-v4.1-Flash-1017". slopinthebag, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol (the author writes "sol 6.1") as their only model.
- Favorable
After switching to Sol 6.1, it finished the whole task in around 2 days, cost around $50
Comment on "500B tokens later: Letting AI agents decompile a first-person shooter". aetherspawn, Hacker News commenter, self-described, Oct 11, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") on a long reverse-engineering task, against Sonnet.
- Favorable
sol 6.1, best bang for buck
Comment on "Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto line". potsandpans, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (the author writes "sol 6.1") decompiling a PlayStation game, against Opus and Astra.
- Favorable
it's much cheaper (as in, subscription usage as well as token costs)
Comment on "DeepSeek-v4.1-Flash-1017". egeozcan, Hacker News commenter, self-described, Oct 23, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") for review loops, against Opus 5.5.
- Favorable
It does so much for so little cost.
Comment on "Gemini 4 Argon". mattmaroon, Hacker News commenter, self-described, Oct 13, 2026. GPT-6.1 Sol (the author writes "6.1 sol") as main model on Hermes.
- Unfavorable
the same type of development tasks appear to consume substantially more credits
Urgent: GPT-6.1 Sol consuming Codex credits excessively after recent update. onlymaz, Codex user (GitHub issue author), self-described, Oct 22, 2026. GPT-6.1 Sol in Codex for software development.
- Favorable
Even though 6.1 Sol is more token efficient
GPT 6.1 Sol is insanely slow. Leo (leodev), founder and developer, intern at Mastra (stated in X bio), self-described, Sep 30, 2026. GPT-6.1 Sol in Codex on a subscription, against Opus 5.5 in Claude Code.
Speed 37%
- Unfavorable
6.1 Sol is one of the slowest models I've used
Comment on "DeepSeek-v4.1-Flash-1017". ac29, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") against Opus 5.5 in daily use.
- Unfavorable
6.1 Sol seems good, but is unbearably slow even with 6.1 being more token efficient than 5.5
Comment on "Getting the most out of Opus 5.5 in Claude and Claude Code". nsingh2, Hacker News commenter, self-described, Oct 4, 2026. GPT-6.1 Sol (the author writes "6.1 Sol") on a subscription.
- Favorable
gpt 6.1 sol: took 4m30s for two p1 and one p2 issue
Comment on "DeepSeek-v4.1-Flash-1017". AmazingTurtle, Hacker News commenter, self-described, Oct 17, 2026. GPT-6.1 Sol reviewing a 200-file C++ game engine change, against DeepSeek v4.1 Flash, GLM 5.3 Flash and GPT-5.6 Sol.
- Favorable
Still, it executed quick
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". Jacob Miller (jjcm), working on diffui.ai, formerly Figma (stated in HN profile), self-described, Sep 29, 2026. GPT-6.1 Sol on an image-to-HTML flow against Opus 5.5.
- Favorable
faster per task (2.9 vs 4.9 minutes)
Comment on "DeepSeek V4.1 Flash 1017 (Max)". Tiberium, Hacker News commenter, self-described, Oct 19, 2026. GPT-6.1 Sol (medium) against DeepSeek v4.1 Flash 1017 (max) on Artificial Analysis per-task figures.
- Unfavorable
6.1 sol was noticably major slow down also
Comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". jp_gorman, Hacker News commenter, self-described, Oct 1, 2026. GPT-6.1 Sol against GPT-5.6 Sol on the author's project.
- Unfavorable
Inference speed on 6.1 Sol went to like 20-30 tokens per second
Comment on "Threat of AI share crash puts world financial stability at risk, says IMF". user43928, Hacker News commenter, self-described, Oct 13, 2026. GPT-6.1 Sol (the author writes "6.1 Sol") through OpenAI.
- Unfavorable
Sol 6.1 has run <30 t/s for me for weeks
Comment on "DeepSeek-v4.1-Flash-1017". bitexploder, Hacker News commenter, self-described, Oct 18, 2026. GPT-6.1 Sol (the author writes "Sol 6.1").
- Favorable
Sol 6.1 isn't far behind on completion time for tasks because it's so damn efficient
Comment on "DeepInfer: High-performance inference framework for DeepSeek models". RussianCow, runs a software consultancy (stated in HN profile), self-described, Oct 20, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") on agentic tasks, against DeepSeek V4.1 Flash.
- Unfavorable
GPT Sol Latest (Sol 6.1) | Slow
Comment on "Samsung TV privacy issues". nekitamo, Hacker News commenter, self-described, Oct 24, 2026. GPT-6.1 Sol (listed as "GPT Sol Latest (Sol 6.1)") in Claude Code on a crackme reverse-engineering benchmark.
- Favorable
using Sol 6.1 in Ultrafast is noticeably faster than DS 4.1 Flash in real world tasks
Comment on "DeepInfer: High-performance inference framework for DeepSeek models". e1g, Hacker News commenter, self-described, Oct 20, 2026. GPT-6.1 Sol in Ultrafast mode (the author writes "Sol 6.1 in Ultrafast"), against DeepSeek 4.1 Flash.
- Favorable
GPT Sol 6.1 is however, for me the most efficient model, both in terms of time to finish and token usage
Comment on "MiniMax M3.1 Flash". sinuhe69, Hacker News commenter, self-described, Oct 19, 2026. GPT-6.1 Sol (the author writes "GPT Sol 6.1").
- Unfavorable
6.1 Sol though is horribly slow
Comment on "Show HN: Open-source model routing for coding agents at Astra-level performance". conception, Hacker News commenter, self-described, Oct 1, 2026. GPT-6.1 Sol (the author writes "6.1 Sol").
- Unfavorable
Sol 6.1 is quite good, but damn is it slow
Comment on "Gemini 4 Argon". onlyrealcuzzo, Hacker News commenter, self-described, Sep 30, 2026. GPT-6.1 Sol (the author writes "Sol 6.1") for overnight tasks.
- Unfavorable
Trivial Git cleanup took approximately 11 minutes.
[Regression] GPT-6.1 Sol: 11-minute trivial Git cleanup and unrequested scope expansion. mhanayama, Codex user (GitHub issue author), self-described, Oct 23, 2026. GPT-6.1 Sol as a Codex coding agent.
- Unfavorable
GPT 6.1 Sol is insanely slow
GPT 6.1 Sol is insanely slow. Leo (leodev), founder and developer, intern at Mastra (stated in X bio), self-described, Sep 30, 2026. GPT-6.1 Sol in Codex on a subscription, against Opus 5.5 in Claude Code.
- Unfavorable
GPT-6.1 Sol has felt slow to me
GPT-6.1 Sol has felt slow to me. Kai Wang (hqmank), AI builder (stated in X bio), self-described, Oct 4, 2026. GPT-6.1 Sol in coding tools.
- Unfavorable
Speed went drastically down again
GPT 6.1 Sol in last couple of hours is not usable. Dawid Skinder, designer and manager who leads creative and dev teams in Web3 and fintech (stated in X bio), self-described, Oct 25, 2026. GPT 6.1 Sol.
- Favorable
compared to 6.1 Sol that completes the same thing at Low thinking in 4 minutes
Findings for my memory project. Liam Debono (leeloumt), builds AI tools, Project Memory and OperAI (stated in X bio), self-described, Oct 22, 2026. GPT-6.1 Sol at Low thinking against GPT-6 Luna on a memory project.
Reliability 13%
- Unfavorable
I've hit model not available limits for GPT 6.1 Sol multiple times over the last week
Comment on "GPT‑6 and Intelligent UI for everyone". wincy, Hacker News commenter, self-described, Oct 7, 2026. GPT-6.1 Sol on a $200 Pro plan and a Codex enterprise connection.
- Unfavorable
it frequently fails with the "model at capacity" error
Comment on "Threat of AI share crash puts world financial stability at risk, says IMF". user43928, Hacker News commenter, self-described, Oct 13, 2026. GPT-6.1 Sol (the author writes "6.1 Sol") through OpenAI.
- Unfavorable
Even last night I still received constant capacity messages halting codex over a dozen times
Comment on "DeepSeek-v4.1-Flash-1017". bitexploder, Hacker News commenter, self-described, Oct 19, 2026. GPT-6.1 Sol Medium (the author writes "Sol 6.1 Medium") in Codex workflows.
- 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, self-described, Oct 13, 2026. GPT-6.1 Sol (the author writes "sol 6.1") in Codex for overnight runs.
- Unfavorable
Since October 25, GPT-6.1 Sol intermittently enters several-minute retry waits
macOS: GPT-6.1 Sol 429 causes long Thinking waits; captured turn_rate_limit_exceeded. Xiao-La, Codex App user on ChatGPT Plus (GitHub issue author), self-described, Oct 26, 2026. gpt-6.1-sol at high reasoning effort in the Codex App on macOS.
- Unfavorable
it unexpectedly returns this capacity error and interrupts the ongoing task
GPT-6.1 Sol (xhigh) repeatedly hits "Selected model is at capacity" during long tasks. zmjjcjb, Codex App user on ChatGPT Plus (GitHub issue author), self-described, Oct 26, 2026. GPT-6.1 Sol at xhigh in the Codex App.
- Unfavorable
GPT 6.1 Sol in last couple of hours is not usable
GPT 6.1 Sol in last couple of hours is not usable. Dawid Skinder, designer and manager who leads creative and dev teams in Web3 and fintech (stated in X bio), self-described, Oct 25, 2026. GPT 6.1 Sol.
- Favorable
OpenAI gpt 6.1 sol could reach almost 99.9% of availability
dotnet__ on Kimi 429s against GPT-6.1 Sol availability. dotnet__, X user who load-balances several coding plans (stated in the post), self-described, Oct 24, 2026. OpenAI GPT-6.1 Sol against Kimi plans, under the author's own load.