Cost
$1.04per 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 Sol
An earlier OpenAI Sol release. OpenAI points to GPT-6.1 Sol as the newer Sol model.
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.You are on GPT-6 Sol. Current:GPT-6.1 Sol
- GPT LunaOpenAI's most efficient GPT model tier for focused, high-volume tasks.GPT-6 Luna
- GPT AstraOpenAI's highest-capability GPT model tier.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
- Offered in
- 5 products
- Made by
- OpenAI
- Family
- GPT Sol, version 6
- Released
- Sep 22, 2026 Legacy
- In its family
- Release 2 of 3 in GPT Sol. The newest is GPT-6.1 Sol.
Strengths and weaknesses
Compare with other models Up to 3 beside GPT-6 Sol
- GPT-6 Sol
Suggested comparisons
The models a buyer weighs against GPT-6 Sol, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside GPT-6 Sol.
GPT-6 Sol
Ranked against the 40 current releases on this chart, GPT-6 Sol ranks 6th of 31 on Factuality, 6th of 29 on Math and 8th of 39 on Long context. On Computer use, OpenAI's own figures on OSWorld 2.0 put GPT-6 Sol 11.7 points above GPT-6 Luna and 5.8 points under Claude Opus 5. It ranks lowest on Answers in full, 20th of 26. Instruction following: not yet published by OpenAI or any independent evaluator, checked Nov 2, 2026.
Each axis is one public benchmark at one setting, on its own fixed 0 to 100 scale, so adding a model never moves another. A dotted bridge crosses a missing result, which is never a zero. A hollow mark is a result from another source: the maker's own figure or another lab's run, where the benchmark's usual source has not tested the model yet. The readout names it.
On the chart
- GPT-6 SolThis pageResults on 11 of 12 axes$2 / $10112 tokens/sFirst token in 106 s
Prices and speeds read between Oct 26, 2026 and Oct 28, 2026.
GPT-6 Sol on each axis11 of 12 with a result
The share of Terminal-Bench 4.0's long terminal tasks the model finishes on its own: services, kernels, proofs and data pipelines, graded on the final artifact with no partial credit.
Terminal-Bench 4.0, pass@1 averaged over 3 runs, mini-swe-agent harness
- GPT-6 Sol44.4%
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 Sol57.6%
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 Sol89.8%
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 Sol94.3%
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 Sol47.9%
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 Sol61.6%
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 Sol64.4%reported by OpenAIBenchmark: OSWorld 2.0, partial reward, offline set, v2026.08.08 release. From another source, so it is drawn and marked but not ranked with the others.OpenAI's own run at maximum reasoning effort, from its launch chart, at $3.25 per task.
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 Sol83.7%
The share of MMMU-Pro's college-level questions over charts, diagrams and photos the model answers correctly.
MMMU-Pro, overall accuracy, no tools
- GPT-6 Sol82.9%
The share of AA-Omniscience's 6,000 knowledge questions across 42 economically relevant topics the model answers correctly from memory, without search.
AA-Omniscience Accuracy, accuracy, Artificial Analysis run
- GPT-6 Sol54.5%Hallucination rate 60.1% 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 Sol64%SpeechMap tested it through OpenRouter at medium reasoning and counted 22.7% of requests denied and 13.2% 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 SolNot yet published by OpenAI or any independent evaluator, checked Nov 2, 2026
Cost, speed, capacity, quality and accuracy for GPT-6 Sol, with where each figure sits among the 41 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
127tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 109 s
- Whole answer
- 113 s
Capacity
1.05Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 128K
- Reads
- Text, Images
Quality
47.6of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,509 Elo
- Terminal-Bench 4.0
- 43.9%
- Epoch Capabilities Index
- 164
Hallucination
60.1%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
- 54.5%
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 Sol: Cached input.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | GPT-6 Sol | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness | 44.4% | GPT-6 SolEffort: not published. Harness: mini-swe-agent. | Vals.ai | Oct 24, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 57.6% | GPT-6 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 89.8% | Effort: max. Harness: none. | Epoch AI | Sep 22, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 94.3% | Effort: max. Harness: none. | Epoch AI | Sep 22, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 47.9% | GPT-6 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | 61.6% | GPT-6 Sol (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness. | Artificial Analysis | Oct 28, 2026 |
| Computer use | OSWorld 2.0Partial reward, offline set, v2026.08.08 release. OpenAI's own run at maximum reasoning effort, from its launch chart, at $3.25 per task.Stands in for OSWorld 2.1, partial score, full 108-task set, v2.1 release, which has no run of GPT-6 Sol yet. | 64.4% | GPT-6 Sol (max)Effort: max. Harness: OpenAI computer-use harness. | OpenAIReported by OpenAI | Sep 22, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 83.7% | GPT-6 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 82.9% | GPT-6 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 54.5%Hallucination rate 60.1% in the same run (lower is better) | GPT-6 Sol (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 27, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. SpeechMap tested it through OpenRouter at medium reasoning and counted 22.7% of requests denied and 13.2% evaded. | 64%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 | Not yet published by OpenAI or any independent evaluator, checked Nov 2, 2026 |
Price and speed
- GPT-6 Sol lists at $2 per million input tokens and $10 per million output tokens. OpenAI pricing, Oct 26, 2026.
- GPT-6 Sol, at max effort, writes 111.7 output tokens per second on OpenAI's API, and its first token arrives 106 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 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-6.1 Terra | 49.5% | 55.1% | 90.9% | 94.3% | 46.2% | 60.2% | 74.2%Reported by OpenAIOSWorld 2.1 | 82.7% | 84.7% | 47.6% | Not yet published | 74.2% |
| ||||||||||||
| GPT-6.1 Sol | 55.1% | 54.2% | 93.7% | 95.4% | 52.9% | 64.9% | 78%Reported by OpenAIOSWorld 2.1 | 83% | 86% | 61.8% | 69.5% | 82% |
| ||||||||||||
| GPT-6 Luna | 13.6% | 54.6% | 78.9% | 90.5% | 38.5% | 53.2% | 48.9%Run by AnthropicOSWorld 2.1 | 83.3% | 79.7% | 39.6% | 63.4% | Not yet published |
| ||||||||||||
| GPT-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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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-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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 Sol94.3%
- GPT-6.1 Terra94.3%
- 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-6 Sol83.7%
- GPT-5.6 Luna83.7%
- 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 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 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. | 10,155 | GPT-6 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. | $0.51 | GPT-6 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. | $0.19 | GPT-6 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. | $0.73 | GPT-6 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. | $0.31 | GPT-6 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. | $0.21 | GPT-6 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. | $1.04 | GPT-6 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. | $1,536 | GPT-6 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. | 31,000 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 20,845 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Speed | ||||
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 113 s | GPT-6 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. | 109 s | GPT-6 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. | 127 tokens/s | GPT-6 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. | 245 s | GPT-6 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. | 109 s | GPT-6 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. | 60.1% | Max effort | Artificial Analysis | Oct 27, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 54.5% | Max effort | Artificial Analysis | Oct 27, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 27.1 | GPT-6 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. | 60.7% | Max effort | Epoch AI | Sep 22, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,477 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it. | 54.3% | Max effort | Mercor (via Epoch AI) | Oct 26, 2026 |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 25.2% | GPT-6 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. | 1,509 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| MLCR (AA run)AA's MLCR overall score for long, multi-document reading. | 33.9% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Vending-Bench 2Vending-Bench 2 final balance of a simulated vending business run by the model, as Epoch AI republishes it. | $14,428 | Andon Labs (via Epoch AI) | Oct 26, 2026 | |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 83.7% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it. | 2,462 | 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. | 89.6% | Max effort | ARC Prize Foundation (via Epoch AI) | Oct 26, 2026 |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 56% | Max effort | Epoch AI | Oct 13, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 30.9% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 97.3% | 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. | 164 | GPT-6 Sol | Epoch AI | Oct 26, 2026 |
| FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run. | 90% | Max effort | Epoch AI | Sep 22, 2026 |
| FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run. | 89.8% | Max effort | Epoch AI | Sep 22, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 94.3% | Max effort | Epoch AI | Sep 22, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 47.9% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 47.6 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents. | 49.4% | GPT-6 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. | 59.1 | Max effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 82.9% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run. | 56% | Max effort | Epoch AI | Sep 22, 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 22, 2026 |
| ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it. | 83% | Vals AI (via Epoch AI) | Oct 26, 2026 | |
| SciCode (AA run)SciCode subproblem accuracy in AA's run. | 57.6% | GPT-6 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. | 43.9% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness. | 30% | GPT-6 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. | 1,689 | Max effort | LMArena (via Epoch AI) | Oct 26, 2026 |
| WeirdML v3, best runWeirdML v3 maximum performance across runs, as Epoch AI republishes it. | 27.6% | Extra-high effort | Håvard Tveit Ihle (via Epoch AI) | Oct 26, 2026 |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 54.4 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 48.6 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 48.6 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points. | 46.2 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 51.1 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 52.5 | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
| Harvey Legal Lab (AA run)AA's run of Harvey's legal task lab. | 3.6% | GPT-6 Sol (Max) | Artificial Analysis | Oct 27, 2026 |
Routes, prices and uptime
Where GPT-6 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 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-sol | us./global. profiles on bedrock-runtime; bedrock-mantle; EOL not sooner than Sept 22, 2027; tiers: Standard only | Amazon Web Services, Models at a glanceAmazon Web Services, GPT-6 Sol |
| Codex | Available | gpt-6-sol | Codex says to switch to gpt-6-sol when available to the plan and client; not in the recommended list | OpenAI, Models |
| Databricks | Available | system.ai.gpt-6-sol | Databricks' supported-models page, read Oct 30, 2026, lists GPT-6 Sol as system.ai.gpt-6-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 Sol. | Databricks, Databricks-hosted inferenceDatabricks, Detailed list of models supported by Databricks Foundation Model APIs |
| The maker's own API | Available | gpt-6-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 Sol ModelOpenAI, GPT-6.1 Sol ModelOpenAI, GPT-6 Luna Model |
| GitHub Copilot | Available | not statedpicker label GPT-6 Sol | available (GA) | GitHub |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub, GitHub Models |
| Microsoft Foundry | Available | gpt-6-sol | listed in GPT-6 series | Microsoft, Foundry Models sold by AzureMicrosoft, Region availability for Foundry Models sold by Azure |
| OpenCode | Available | gpt-6-sol | OpenCode Zen, OpenAI Responses endpoint | Anomaly (OpenCode), ModelsOpenCode (Anomaly) |
| OpenRouter | Available | openai/gpt-6-sol | 1,050,000 / 128,000; batch variant listed | OpenRouter |
| Snowflake Cortex | Preview | openai-gpt-6-sol | Private preview | Snowflake |
| Windsurf / Devin | Available | gpt-6-sol-highgpt-6-sol-high-prioritygpt-6-sol-lowgpt-6-sol-low-prioritygpt-6-sol-maxgpt-6-sol-max-prioritygpt-6-sol-mediumgpt-6-sol-medium-prioritygpt-6-sol-nonegpt-6-sol-none-prioritygpt-6-sol-xhighgpt-6-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.
| 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 | $0.2 | Blended $4, 3 input : 1 output, no cacheBlended $1.54, 7 cache-hit : 2 input : 1 outputCache write $2.50 | Artificial Analysis, Oct 27, 2026 |
Lineup
OpenAI's 12 releases in 7 families, oldest to newest along each tier, with list price and speed. GPT-6 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
- This page6Legacy. In 5 products we coverPrice$2 / $10Speed111.7 tok/s
- 6.1Current. 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
Products
We cover 5 products that offer GPT-6 Sol today: 4 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.
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.
Plan access as each vendor's page states it: GitHub (Oct 31, 2026), OpenAI (Oct 28, 2026).
Comparisons
GILD comparisons that name GPT-6 Sol, then those of the clouds and APIs that serve it.
- Claude Code vs Codex: Which Agentic Coding Workflow Fits Your Team?Names GPT-6 Sol
- Codex vs GitHub Copilot: ChatGPT-Bundled Agent or GitHub-Native Platform?Names GPT-6 Sol
- Amazon Bedrock vs Claude API: Buying Claude Through AWS or From AnthropicCompares routes that serve GPT-6 Sol
- Amazon Bedrock vs Microsoft Foundry: Which Cloud AI Platform Fits Your Stack?Compares routes that serve GPT-6 Sol
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Compares routes that serve GPT-6 Sol
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve GPT-6 Sol
- Gemini API vs Amazon Bedrock: One Model Family or a Model Marketplace?Compares routes that serve GPT-6 Sol
- Gemini Enterprise Agent Platform vs Microsoft Foundry: Google Cloud or Azure for Models and AgentsCompares routes that serve GPT-6 Sol
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve GPT-6 Sol
- OpenAI API vs Azure OpenAI: Same Models, Different ContractsCompares routes that serve GPT-6 Sol
- OpenAI API vs Gemini API: Who Finishes the Task for Less?Compares routes that serve GPT-6 Sol
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Compares routes that serve GPT-6 Sol
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve GPT-6 Sol
What practitioners report
Strongest on Speed, weakest on Reliability.
Each figure is the share of accounts naming GPT-6 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. | 31% | 10 favorable, 22 not, 32 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 56% | 5 favorable, 4 not, 9 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | Only concerns on record | 0 favorable, 3 not, 3 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | 25% | 3 favorable, 9 not, 12 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 55% | 12 favorable, 10 not, 21 authors |
| SpeedResponse time, time to first token, and throughput. | 57% | 4 favorable, 3 not, 7 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 17% | 1 favorable, 5 not, 6 authors |
Every model on these seven axes
| Axis | GPT-6 Sol | GPT-6.1 Terra | GPT-6.1 Sol | 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-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 | 31%10 favorable, 22 not, 32 authors | 33%3 favorable, 6 not, 8 authors | 55%12 favorable, 10 not, 22 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 | 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 | 56%5 favorable, 4 not, 9 authors | 40%2 favorable, 3 not, 5 authors | 40%4 favorable, 6 not, 10 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 | 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 | Only concerns on record0 favorable, 3 not, 3 authors | Only concerns on record0 favorable, 1 not, 1 author | 38%3 favorable, 5 not, 8 authors | 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 | 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 | 25%3 favorable, 9 not, 12 authors | Only concerns on record0 favorable, 2 not, 2 authors | 27%3 favorable, 8 not, 11 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 | 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 | 55%12 favorable, 10 not, 21 authors | 80%8 favorable, 2 not, 9 authors | 74%14 favorable, 5 not, 19 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 | 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 | 57%4 favorable, 3 not, 7 authors | 83%5 favorable, 1 not, 5 authors | 37%7 favorable, 12 not, 19 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 | 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 | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | 13%1 favorable, 7 not, 8 authors | Only concerns on record0 favorable, 5 not, 5 authors | 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 | 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 76 accounts behind GPT-6 Sol's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis and the web for accounts that name GPT-6 Sol.
Quality and reasoning 31%
- Unfavorable
6-Sol is noticeably worse for code reviews (worse than Deepseek 4.1 flash), has implementation issues
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". wkcheng, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol for code review and feature work, side by side with Opus 5.5.
- Unfavorable
I have been running Sol at max thinking and it is about the same as old Luna with max thinking, give or take. Sometimes feeling even dumber.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". nicce, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol at max thinking.
- Unfavorable
Sonnet 5.5 is way better than GPT 6 Sol.
Hacker News comment on "Sonnet 5.5". jdw64, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Sol on the Codex Pro plan.
- Unfavorable
GPT-6-Sol is markedly worse than GPT-5.6-Sol
Hacker News comment on "Tell HN: Codex Is Down [fixed]". OutOfHere, Hacker News commenter, self-described, Sep 25, 2026. GPT-6 Sol in day-to-day work.
- Unfavorable
My own experience likewise shows 6.0 making loads of silly mistakes
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". unsupp0rted, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written GPT 6.0 Sol) in coding work.
- Unfavorable
it didn't felt as good as Sol, and the benchmarks also showed it was a bit worse than the previous Sol release
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". coopykins, Hacker News commenter, self-described, Sep 30, 2026. GPT-6 Sol in coding work.
- Favorable
GPT 6 Sol still gets the job done for anything that doesn't require design thinking
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". mchusma, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol for serious work, against Opus 5.5.
- Unfavorable
mildly disappointed with GPT-6 Sol and Luna not improving intelligence and only cutting the price
Hacker News comment on "Claude Code reads AGENTS.md only when telemetry is on [fixed]". user43928, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol and GPT-6 Luna in the Codex app.
- Unfavorable
GPT-6 Sol was underwhelming
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". Alifatisk, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol through the API and Codex.
- Unfavorable
MiMo V2.6 Pro performs better and is cheaper than GPT 6 Sol on my benchmark
Hacker News comment on "GPT-6 Sol and Luna". dom96, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Sol on his own benchmark.
- Unfavorable
Sol 6 is a heaping pile of garbage. Just epic levels of slop.
Hacker News comment on "GPT-6 Sol and Luna". cmrdporcupine, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol (written Sol 6) in Codex.
- Unfavorable
In my work it makes way too many mistakes to be useful
Hacker News comment on "GPT-6 Sol and Luna". ReEnvisionAI, Hacker News commenter, self-described, Sep 24, 2026. GPT-6 Sol with Astra review passes.
- Unfavorable
I've never seen such a large degradation in intelligence in a model until I tried out Sol 6
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". koyote, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol 6) after weeks on GPT-5.6 Sol.
- Unfavorable
Huge regression compared to Sol 5.6, often doing really dumb things.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". the_duke, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol 6) for coding.
- Unfavorable
It re-implemented some wrapper components in a simplified way that lost some of the UI
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". notatoad, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol at xhigh in Codex, side by side with Opus 5.5 high.
- Unfavorable
hallucinated several facts despite me asking beforehand to check online
Hacker News comment on "Sonnet 5.5". cromka, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Sol (written GPT6 Sol) in a coding session.
- Unfavorable
I'm deliberately avoiding Sol 6 right now due to some issues with hallucinations
Hacker News comment on "Newgrounds.com – A community of games, music, and art". Gareth321, Hacker News commenter, self-described, Oct 3, 2026. GPT-6 Sol (written Sol 6), avoided in favor of GPT-5.6 Sol.
- Unfavorable
I even set gpt-6-sol/max on the problem and even it failed to fix my npm installation
Hacker News comment on "Pig: Pi in Go, a port that plans on keeping up". Bowes-Lyon, Hacker News commenter, self-described, Sep 27, 2026. gpt-6-sol at max effort.
- Unfavorable
Generated code (I mostly program C++) is often bloated and not succinct or "simple" enough to my tastes, so it requires multiple rounds of cleanup
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". naikon, Hacker News commenter, self-described, Sep 30, 2026. gpt-6-sol mostly through the GitHub Copilot CLI, C++.
- Favorable
In my testing yesterday GPT 6 Sol still beat Opus 5.5 on code review
Hacker News comment on "ChatGPT Pro 500". alasano, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol for code review.
- Favorable
GPT 6 Sol is still better and 2x cheaper in my benchmarks
Hacker News comment on "Claude Opus 5.5". XCSme, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol against Opus 5.5 high on his aibenchy comparison.
- Favorable
In code, GPT-6 Sol dominates it: also 10/10, but with a higher quality score
Hacker News comment on "Ember-1". 7777777phil, Hacker News commenter, self-described, Sep 27, 2026. GPT-6 Sol on his model-router benchmark.
- Favorable
I don't really find 6 Astra to be significantly better than 6/6.1 Sol for general coding
Hacker News comment on "Show HN: Open-source model routing for coding agents at Astra-level performance". YuechenLi, Hacker News commenter, self-described, Oct 1, 2026. GPT-6 Sol against GPT-6.1 Sol and GPT-6 Astra in general coding.
- Favorable
it hasn't felt like 6 Sol was much of a regression from 6 Astra
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". ChaseRensberger, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written 6 Sol) against GPT-6 Astra.
- Favorable
after every task I ask Sol to review it and it catches most of them
Hacker News comment on "Claude Opus 5.5". knapcio, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol (written Sol 6) reviewing Opus 5.5 output.
- Favorable
producing way worse result than Sol-6
Hacker News comment on "Sonnet 5.5". fallingbananna, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol-6) on the Pacman bake-off.
- Unfavorable
both models have been very bad for openAI's Sol brand
Hacker News comment on "Kimi K3.1 Pro and K3.1 Pro Highspeed". fancyfredbot, Hacker News commenter, self-described, Oct 23, 2026. GPT-6 Sol (written 6 Sol) and GPT-6.1 Sol.
- Unfavorable
I have experienced GPT-6 Sol as less attentive and less proactive than GPT-5.6 Sol across my everyday work.
[Codex App] GPT-6 Sol context and task-completion omissions: three paired audits vs GPT-5.6 Sol. igor-markin, GitHub issue author, self-described, Sep 24, 2026. GPT-6 Sol at max reasoning in the Codex app, paired against GPT-5.6 Sol.
- Unfavorable
then made an unsolicited second `ask_user` call with two more questions (platform and note format)
GPT-6-sol compact scope adds an unsolicited second interview. FasalZein, GitHub issue author, self-described, Sep 25, 2026. openai-codex/gpt-6-sol in the pi-ask behavior harness, full and compact modes.
- Favorable
a few issues but generally functional and running
New dev. / Actual results using 6-Sol - med/high.. PlasmaChroma, r/codex poster, self-described, Sep 25, 2026. GPT-6 Sol (written 6-Sol) at medium and high in Codex, executing an eight-phase plan.
- Unfavorable
I tried GPT 6 Sol but it was so horrendously bad that I went back to 5.6 Sol.
In your experience, is it worth it to switch from 5.6 Sol to 6.1 Sol?. skilliard7, r/codex poster, self-described, Oct 13, 2026. GPT 6 Sol tried in place of GPT-5.6 Sol through the API.
- Favorable
GPT-6 found 35+ bugs, while Opus 5.5 found only a few.
GPT-6 Sol and Opus 5.5 whole-codebase bug review. pcshipp, self-described software engineer building mobile and web apps, Oct 12, 2026. GPT-6 Sol reviewing the author's entire codebase against Opus 5.5.
Tool use and structured output 56%
- Unfavorable
in a panic response to poor agentic capabilities of 6
Hacker News comment on "GPT‑6 and Intelligent UI for everyone". exitb, Hacker News commenter, self-described, Oct 7, 2026. GPT-6 Sol (written 6 Sol) agentic use.
- Favorable
Seemed to work just fine when Astra used it in Codex as subagents.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". jstummbillig, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol 6) as Codex subagents under Astra.
- Favorable
with those rows, GPT-6 Sol and Luna tools and `json_schema` work on main
[Bug]: Bedrock GPT-6 Sol/Luna tools are dropped on Converse, and temperature returns 400 even with drop_params. kimnamu, GitHub issue author, self-described, Sep 23, 2026. GPT-6 Sol on Amazon Bedrock through the LiteLLM proxy.
- Unfavorable
When a gpt-6 model (OpenAI) is selected, any chat request that needs tool calling fails.
[Bug]: Chat fails with gpt-6 models (gpt-6-luna, gpt-6-sol): "Function tools with reasoning_effort are not supported". haru, owner of the redmine_ai_helper repository, self-described, Oct 3, 2026. gpt-6-sol through RubyLLM 1.16 on Chat Completions in the Redmine AI Helper plugin.
- Unfavorable
GPT-6 models then reject function tool calls on `/v1/chat/completions` with a 400 unless `reasoning_effort` is set to `"none"`
GPT-6 models get no default reasoning settings leading to 400 on /v1/chat/completions with function tools. lminaudier, GitHub issue author, self-described, Oct 8, 2026. gpt-6-sol through the OpenAI Agents SDK 0.19.2 on /v1/chat/completions.
- Favorable
GPT-6 Sol as orchestrator ([gpt6-sol.md](../blob/main/reports/2026-09-28-orchestrator-and-penalty/gpt6-sol.md), #118) was local-first GO at `aggressive` (7/7 dispatched, 7/7 passing)
GPT-6 Sol at balanced, and n ≥ 5 per cell. Starefossen, GitHub issue author, self-described, Sep 28, 2026. GPT-6 Sol as orchestrator in a local-first agent benchmark at aggressive level.
- Favorable
Both calls succeeded; neither mode had validation errors.
GPT-6-sol compact scope adds an unsolicited second interview. FasalZein, GitHub issue author, self-described, Sep 25, 2026. openai-codex/gpt-6-sol in the pi-ask behavior harness, full and compact modes.
- Favorable
Then 6-Sol was basically left to execute mostly on its own with some gentle prodding.
New dev. / Actual results using 6-Sol - med/high.. PlasmaChroma, r/codex poster, self-described, Sep 25, 2026. GPT-6 Sol (written 6-Sol) at medium and high in Codex, executing an eight-phase plan.
- Unfavorable
Astra/SOL 6 will refuse things that are valid. In this case visually inspecting HTML file via file://
SOL/Astra 6 Unable to visually inspect local HTML files. MadBoyEvo, r/codex poster, self-described, Sep 23, 2026. GPT-6 Sol at High in Codex, inspecting a local HTML file over file://.
Long context Only concerns on record
- Unfavorable
it keeps forgetting the changes it did itself; no context compaction was used
Hacker News comment on "Sonnet 5.5". cromka, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Sol (written GPT6 Sol) in a coding session.
- Unfavorable
Cache doesn't help you much when you are compacting every 5 minutes
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". joshstrange, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol at medium in Codex on a $100 plan, replying to a comment on GPT-6 Sol cache pricing.
- Unfavorable
Needle recall at 690K–909K is inconsistent on Sol and Luna, even though acceptance is consistent.
[Codex OAuth] Live receipts: gpt-6-sol/luna accept ~909K input (rejects ~995K); mark -900k variants verified. myagizmaktav, GitHub issue author, self-described, Sep 28, 2026. gpt-6-sol through Codex OAuth at low reasoning, inputs up to about 909K tokens.
Developer experience 25%
- Unfavorable
it ignores all of my AGENTS.md, which is short and concise. I mean I point it at ignoring it, it acknowledges and ignores again.
Hacker News comment on "Sonnet 5.5". cromka, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Sol (written GPT6 Sol) in a coding session.
- Favorable
I kinda prefer Sol, it seems like a more patient and thorough model, especially Sol 6
Hacker News comment on "Best LLM for every budget, updated daily". bitexploder, Hacker News commenter, self-described, Sep 24, 2026. GPT-6 Sol (written Sol 6) as a reviewer in an agent loop.
- Favorable
GPT 6 Sol / GPT 6 Luna are my bread and butter and spec-driven design works great
Hacker News comment on "Coding is not solved". spicyusername, Hacker News commenter, self-described, Sep 29, 2026. GPT 6 Sol and GPT 6 Luna across 5 to 20 agents.
- Favorable
now I'm on GPT-6 Sol. It's been a very good experience.
Hacker News comment on "Meta and Microsoft take steps to reduce employee usage of Claude AI". hbn, Hacker News commenter, self-described, Oct 7, 2026. GPT-6 Sol in the GitHub Copilot app at work.
- Unfavorable
Like are you supposed to just somehow intuit , "ah yeah, this task is definitely a GPT-6 Sol Medium task," or something?
Hacker News comment on "GPT-6 Sol and Luna". adamrezich, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Sol effort levels in Codex beside the other GPT-6 and GPT-5.x models.
- Unfavorable
in my experience using luna and sol 6 today, they are incredibly aggravating to work with
Hacker News comment on "GPT-6 Sol and Luna". Aeolun, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol (written sol 6) and Luna on launch day.
- Unfavorable
I was getting insanely annoyed at how misaligned it is
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". rrvsh, Hacker News commenter, self-described, Sep 30, 2026. GPT-6 Sol (written 6 Sol) trialled for three days.
- Unfavorable
GPT-6 Sol tends to rabbit hole and over engineer things.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". pampas, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol in coding work.
- Unfavorable
Sampling is still broken there: on Converse, GPT-6 Sol, Luna and Astra get a Bedrock 400 for `temperature` or `top_p` even with `drop_params: true`
[Bug]: Bedrock GPT-6 Sol/Luna tools are dropped on Converse, and temperature returns 400 even with drop_params. kimnamu, GitHub issue author, self-described, Sep 23, 2026. GPT-6 Sol on Amazon Bedrock through the LiteLLM proxy.
- Unfavorable
Go's GPT-6 capability path sets supportsNonReasoningParameters false for every GPT-6 model, stripping permitted controls and emitting misleading warnings.
fix(openai): retain supported non-reasoning sampling for GPT-6 Sol and Luna. nrbrd, GitHub issue author, self-described, Oct 20, 2026. GPT-6 Sol through the Grafana Go AI SDK with reasoning effort none.
- Unfavorable
so GPT-6 Sol, Luna and 6.1 Sol can't take an effort level
[BUG] harness: Bedrock GPT-6 Sol, Luna and 6.1 Sol reject effort levels, and Astra effort "off" fails. Katsuhito04, GitHub issue author, self-described, Oct 15, 2026. us.openai.gpt-6-sol on Amazon Bedrock through the Strands harness.
- Unfavorable
when I tried to disallow over -engineering on gpt 6 sol, it still keeps over-engineering a bit?
Gpt 6 Sol vs. Gpt 5.6 Sol. Cryptoshiii, r/codex poster, self-described, Oct 13, 2026. GPT-6 Sol (written gpt 6 sol) in coding work.
Cost 55%
- Unfavorable
On top of that, the usage allowance has dropped way too much.
Hacker News comment on "Sonnet 5.5". jdw64, Hacker News commenter, self-described, Sep 28, 2026. GPT-6 Sol on the Codex Pro plan.
- Favorable
Surprising how cheap Sol 6 was.
Hacker News comment on "Sonnet 5.5". coopykins, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol-6) pricing in use.
- Favorable
I can probably use Sol 6 as much as I want in the week
Hacker News comment on "GPT-6 Sol and Luna". mchusma, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Sol (written Sol 6) on a weekly subscription allowance.
- Unfavorable
It was basically GPT-5.6 Terra for the price of Sol.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". Alifatisk, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol through the API and Codex.
- Unfavorable
25% more expensive in practice
Hacker News comment on "GPT-6 Sol and Luna". XCSme, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol at high on his aibenchy comparison.
- Favorable
GPT 6 Sol is still better and 2x cheaper in my benchmarks
Hacker News comment on "Claude Opus 5.5". XCSme, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol against Opus 5.5 high on his aibenchy comparison.
- Favorable
but with a higher quality score and a lower estimated cost
Hacker News comment on "Ember-1". 7777777phil, Hacker News commenter, self-described, Sep 27, 2026. GPT-6 Sol on his model-router benchmark.
- Unfavorable
6.1 Sol is a lot more token efficient than 6 Sol
Hacker News comment on "Show HN: Open-source model routing for coding agents at Astra-level performance". YuechenLi, Hacker News commenter, self-described, Oct 1, 2026. GPT-6 Sol against GPT-6.1 Sol and GPT-6 Astra in general coding.
- Favorable
I've been using it exclusively since release and it feels like a cheaper astra to me
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". ChaseRensberger, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written GPT 6.0 Sol), used exclusively since release.
- Favorable
it did cost 4 times as much, while producing way worse result than Sol-6
Hacker News comment on "Sonnet 5.5". fallingbananna, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol-6) on the Pacman bake-off.
- Unfavorable
I was shocked at how quickly I ran out my $100/mo subscription with a single agent (sol medium).
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". joshstrange, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol at medium in Codex on a $100 plan, replying to a comment on GPT-6 Sol cache pricing.
- Favorable
OpenAI have been achieving even more impressive optimizations, hence why GPT-6 Sol and GPT-6 Luna are half the price of their 5.6 equivalents.
Hacker News comment on "Anthropic's IPO prospectus shows AI vision, surging costs". simonw (Simon Willison), Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol and GPT-6 Luna pricing against their GPT-5.6 versions.
- Favorable
they did a phenomenal job getting gpt-6-sol to max out right where Astra begins
Hacker News comment on "GPT-6 Sol and Luna". ComputerGuru, Hacker News commenter, self-described, Sep 22, 2026. gpt-6-sol pricing against GPT-6 Astra.
- Favorable
gpt-6-sol, for instance, dropped price for the same level of intelligence
Hacker News comment on "Tell HN: OpenAI $500 ProMax plan listed in API". sejje, Hacker News commenter, self-described, Sep 25, 2026. gpt-6-sol pricing for its level of intelligence.
- Favorable
6 sol is almost unlimited and I only use xhigh
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". redox99, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written 6 sol) at xhigh on a $100 Codex plan.
- Unfavorable
GPT 6 Sol has less usage than 5.3 Codex
Hacker News comment on "Pacing the Frontier is not the actual goal for AI labs". OliveronData, Hacker News commenter, self-described, Sep 28, 2026. GPT 6 Sol subscription usage allowance.
- Favorable
which is basically 5.6 Sol and Luna, but a bit better and also 50% cheaper
Hacker News comment on "Unreal Agent". NostraDavid, Hacker News commenter, self-described, Sep 22, 2026. GPT-6 Sol against GPT-5.6 Sol in Codex.
- Unfavorable
after approximately **three relatively small code-editing tasks** using **GPT-6 Sol with High reasoning**
[Windows][Plus] GPT-6 Sol High: 5-hour Codex allowance exhausted after three small code-editing tasks (Oct 26). Zokl17, GitHub issue author, self-described, Oct 26, 2026. GPT-6 Sol at High reasoning in Codex Desktop on Windows, ChatGPT Plus.
- Unfavorable
the Work/Codex usage subsequently showed approximately **7% of the 5-hour allowance consumed**
GPT-6 Sol Medium: single
okinteraction consumed ~7% of 5-hour Work/Codex quota. Charonlzw, GitHub issue author, self-described, Sep 30, 2026. GPT-6 Sol at Medium reasoning in Codex Desktop on Windows, ChatGPT Plus. - Unfavorable
was local-first GO at `aggressive` (7/7 dispatched, 7/7 passing) and NO-GO on cost
GPT-6 Sol at balanced, and n ≥ 5 per cell. Starefossen, GitHub issue author, self-described, Sep 28, 2026. GPT-6 Sol as orchestrator in a local-first agent benchmark at aggressive level.
- Favorable
often using less than half the tokens
X post by @flavioAd on early access to GPT-6 Sol. Flavio Adamo, builds a human approval layer for coding agents (stated in X bio), self-described, Sep 22, 2026. GPT-6 Sol with early access, against GPT-5.6.
- Unfavorable
The averages show a bigger gap because GPT 6 Sol had a few very expensive runs.
I ran GPT 6.1 Sol against GPT 6 Sol on 24 tasks from my own repo, and found that it maintained quality while cutting cost in half. bisonbear2, building the Stet coding-agent evaluation tool (stated in the post), self-described, Oct 12, 2026. GPT 6 Sol at medium reasoning in Codex on 24 merged tasks from a Go and TypeScript repo.
Speed 57%
- Unfavorable
which makes it 2x slow3r
Hacker News comment on "GPT-6 Sol and Luna". XCSme, Hacker News commenter, self-described, Sep 23, 2026. GPT-6 Sol at high on his aibenchy comparison.
- Favorable
we meant "GPT 6 Sol" (basically, fast TPS, don't need the limits of intelligence really)
Hacker News comment on "Show HN: Whiteboard (YC W26) – An open-source IDE for thoughtful software design". sidharthkmenon, member of the Whiteboard (YC W26) team replying in its Show HN thread, self-described, Sep 24, 2026. GPT 6 Sol in the Whiteboard app.
- Favorable
6.1 Sol is slower than 6 Sol
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". JacobAsmuth, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol output speed against GPT-6.1 Sol on Artificial Analysis.
- Favorable
The smoking gun is how much slower than Sol 6 this is.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". jauntywundrkind, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol 6) speed against GPT-6.1 Sol.
- Unfavorable
gpt-6-sol is extremely slow to the point it is unusable
GPT-6-sol is extremely slow. shafty023, GitHub issue author, self-described, Sep 29, 2026. gpt-6-sol in Codex CLI 0.159.0 on a Pro 20x plan.
- Unfavorable
Since GPT-6 Sol became available, the same kind of work is often taking around 50 minutes
[Performance] GPT-6 Sol tasks taking 40+ minutes to complete. felixsc321-hub, GitHub issue author, self-described, Sep 23, 2026. GPT-6 Sol in the Codex app on Windows, ChatGPT Plus.
- Favorable
Tasks that took ~1 hour on 5.6 can now take ~20 minutes
X post by @flavioAd on early access to GPT-6 Sol. Flavio Adamo, builds a human approval layer for coding agents (stated in X bio), self-described, Sep 22, 2026. GPT-6 Sol with early access, against GPT-5.6.
Reliability 17%
- Unfavorable
Sol 6 was pretty good the first 4 days or so of it's release. Then it was probably dialed back to a lower effort level and it became really bad.
Hacker News comment on "GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price". spwa4, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written Sol 6) over its first week.
- Unfavorable
Have GPT 5.6 Sol and GP6 6 Sol been nerfed due to the same resource constraints? They have seemed dumber recently.
Hacker News comment on "OpenAI Says It Will Not Release Newest A.I. Model Over Safety Concerns". dash-44, Hacker News commenter, self-described, Sep 29, 2026. GPT-6 Sol (written GP6 6 Sol) and GPT-5.6 Sol.
- Unfavorable
secretly downgrading models to a level that is not reliable anymore is the last straw
Hacker News comment on "Claude Code reads AGENTS.md only when telemetry is on [fixed]". michaellee8, Hacker News commenter, self-described, Sep 23, 2026. gpt-6-sol on a $200 ChatGPT plan, checked with a pelican test.
- Unfavorable
repeatedly returns "Selected model is at capacity. Please try a different model." for GPT-6.1-Sol / GPT-6 Sol, for 7+ hours
Persistent "Selected model is at capacity" on GPT-6.1 Sol / GPT-6 Sol (Codex CLI, Pro). WayneChenDG, GitHub issue author, self-described, Oct 20, 2026. GPT-6 Sol and GPT-6.1 Sol in Codex CLI v0.163.0, desktop and web, ChatGPT Pro.
- Unfavorable
All GPT-6 models available to me in Codex CLI (Luna, Sol, and Astra) incorrectly reject benign prompts such as "hi".
GPT-6 Sol/Luna/Astra falsely reject benign prompts with Invalid prompt safety error. newnew0097-web, GitHub issue author, self-described, Sep 28, 2026. gpt-6-sol, gpt-6-luna and gpt-6-astra in Codex CLI v0.157.1, ChatGPT Pro.
- Favorable
I recommend running it natively in Codex with GPT-6 Sol xhigh ... doesn't seem to be an issue there
X post on gpt-6-sol route behavior. haithum (darkzOGx), X author comparing native Codex with Hermes, self-described, Oct 25, 2026. GPT-6 Sol xhigh running natively in Codex, against daybreak-blue through Hermes.