Cost
$0.96per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at max effort.
- Cached input
- $0.05 per 1M tokens
GPT Terra model by OpenAI
GPT-6.1 Terra
OpenAI's fast, efficient GPT-6.1 model for visual reasoning, computer use and writing, at US$1 per million input tokens and US$5 per million output tokens. Artificial Analysis scores it 51 on its Intelligence Index at US$0.96 per task, and OpenAI's own OSWorld 2.1 computer-use run (offline set) puts it at 74.2%, 3.8 points under GPT-6.1 Sol. API model gpt-6.1-terra, with a 1,050,000-token context and 128,000 output tokens on the OpenAI API.
Where it sits in OpenAI's lineup
- GPT TerraOpenAI's fast, efficient GPT tier for visual reasoning, computer use, and writing.This model
- GPT SolOpenAI's GPT model tier for demanding everyday and agentic work.GPT-6.1 Sol
- GPT LunaOpenAI's most efficient GPT model tier for focused, high-volume tasks.GPT-6 Luna
- GPT AstraOpenAI's highest-capability GPT model tier.GPT-6 Astra
- GPT-5OpenAI's GPT-5 frontier models, released before the Sol, Terra and Luna tiers.GPT-5.5
- gpt-ossOpenAI's open-weight GPT models under the Apache 2.0 license.gpt-oss-120b
- GPT CodexOpenAI's GPT models tuned for agentic coding in Codex.GPT-5.3-Codex
- Stack role
- Foundation Model / Reasoning Engine
- Offered in
- 4 products
- Made by
- OpenAI
- Family
- GPT Terra, version 6.1
- Released
- Oct 26, 2026 Current
- In its family
- The newest of 2 GPT Terra releases.
Strengths and weaknesses
Compare with other models Up to 3 beside GPT-6.1 Terra
- GPT-6.1 Terra
Suggested comparisons
The models a buyer weighs against GPT-6.1 Terra, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside GPT-6.1 Terra.
GPT-6.1 Terra
Among the 40 current releases on this chart, GPT-6.1 Terra ranks 4th of 28 on Math, 5th of 24 on Multimodal and 8th of 31 on Agentic coding. On Computer use, OpenAI's own figures on OSWorld 2.1 put GPT-6.1 Terra 6.7 points under GPT-6 Astra, 3.8 points under GPT-6.1 Sol and 18.7 points above GPT-6 Luna. Answers in full: 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-6.1 TerraThis pageResults on 11 of 12 axes$1 / $5For prompts under 272K tokens; $2 / $7.50 at 272K or more, as OpenRouter lists it.97 tokens/sFirst token in 275 s
Prices and speeds read between Oct 26, 2026 and Nov 2, 2026.
GPT-6.1 Terra 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-6.1 Terra49.5%
The share of SciCode's scientific programming subproblems the model's code solves on the first attempt.
SciCode, subproblem accuracy, pass@1, highest effort run
- GPT-6.1 Terra55.1%
The share of FrontierMath's held-out research-grade problems (tiers 1 to 3) the model answers correctly.
FrontierMath Tiers 1-3, accuracy, pass@1, highest effort run
- GPT-6.1 Terra90.9%
The share of GPQA Diamond's graduate-level biology, chemistry and physics questions the model answers correctly.
GPQA Diamond, accuracy, pass@1, highest effort run
- GPT-6.1 Terra94.3%
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-6.1 Terra46.2%
The share of each AutomationBench task's objectives the model completes by calling REST APIs across simulated business apps (Gmail, Sheets, Slack, Salesforce, Zendesk, Jira, HubSpot), averaged over tasks. A task that breaks one of its policy guardrails scores zero.
AutomationBench-AA, score, Artificial Analysis run
- GPT-6.1 Terra60.2%
How much of each OSWorld 2.1 workflow the model completes by operating a real Ubuntu desktop through screenshots, mouse and keyboard: all 108 long tasks across apps, files, mail and browsers, on the September 2026 v2.1 release of the task files. A point is the mean share of each task's weighted checks the model passes (the partial score, as a percentage). The OSWorld team's own runs come first. Where the team has not run a release, the point is another lab's run or the maker's own published figure, marked with who ran it and the benchmark it ran: OSWorld 2.1 in the maker's harness, OSWorld 2.0's offline set or the earlier OSWorld-Verified. Those points are drawn so the release has a figure, and they are not ranked against the team's runs.
OSWorld 2.1, partial score, full 108-task set, v2.1 release. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- GPT-6.1 Terra74.2%reported by OpenAIBenchmark: OSWorld 2.1, score, offline set, v2.1 release, where the axis reads partial score, full 108-task set. From another source, so it is drawn and marked but not ranked with the others.OpenAI's own run at maximum reasoning effort, from its launch chart, at $1.19 per task. OpenAI does not say whether the score counts partial credit.
The share of AA-LCR's questions the model answers correctly by reasoning across long sets of real documents, about 100K tokens each.
AA-LCR v1.1, accuracy, Artificial Analysis run
- GPT-6.1 Terra82.7%
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-6.1 Terra84.7%
The share of AA-Omniscience's 6,000 knowledge questions across 42 economically relevant topics the model answers correctly from memory, without search.
AA-Omniscience Accuracy, accuracy, Artificial Analysis run
- GPT-6.1 Terra47.6%Hallucination rate 34.5% in the same run (lower is better)
The share of SpeechMap's 2,120 sensitive and controversial but legal requests the model answers in full: arguments, essays and explanations on contested themes in politics, religion, race, sex, history and similar topics, four wordings per theme across 530 themes. SpeechMap's judge rates each response complete, evasive (hedged or redirected), a denial, or an error (the provider's API blocked the request). Only complete answers count, so the point is the share answered in full: 100 minus the share hedged, refused or blocked by the provider. Higher means more lawful requests answered in full. The share blocked at the provider is printed apart in the table, because an API error is not the model declining. Where SpeechMap runs a release both with reasoning off and with reasoning on (a -reasoning or -thinking entry), the reasoning-on entry is used; a release with one entry uses that entry.
SpeechMap, % Complete over 2,120 contested requests, reasoning-on entry
- GPT-6.1 TerraNot yet published by OpenAI or any independent evaluator, checked Nov 2, 2026
The share of MultiChallenge's multi-turn conversations in which the model keeps every instruction it was given earlier in the conversation.
MultiChallenge, accuracy, Scale AI run
- GPT-6.1 Terra74.2%On Oct 28, 2026, Scale AI ranked it 6th, tied with Muse Spark Open.Plus or minus 5.4 points (95% interval)
Cost, speed, capacity, quality and accuracy for GPT-6.1 Terra, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
91tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 78 s
- Whole answer
- 83 s
Capacity
1.05Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 128K
- Reads
- Text, Images
Quality
51.0of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,476 Elo
- Terminal-Bench 4.0
- 55.6%
Hallucination
34.5%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
- 47.6%
Where you can get it
7of 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 and GILD's route matrix, read Oct 27 to Nov 2, 2026. Each measure's definition and source open under . Not yet published for GPT-6.1 Terra: Epoch Capabilities Index.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | GPT-6.1 Terra | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness | 49.5% | GPT-6.1 TerraEffort: not published. Harness: mini-swe-agent. | Vals.ai | Oct 26, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 55.1% | GPT-6.1 Terra (Max)Effort: max. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 90.9% | Effort: max. Harness: none. | Epoch AI | Oct 26, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 94.3% | Effort: max. Harness: none. | Epoch AI | Oct 26, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 46.2% | GPT-6.1 Terra (Max)Effort: max. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | 60.2% | GPT-6.1 Terra (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness. | Artificial Analysis | Nov 2, 2026 |
| Computer use | OSWorld 2.1Score, offline set, v2.1 release. OpenAI's own run at maximum reasoning effort, from its launch chart, at $1.19 per task. OpenAI does not say whether the score counts partial credit.Stands in for OSWorld 2.1, partial score, full 108-task set, v2.1 release, which has no run of GPT-6.1 Terra yet. | 74.2% | GPT-6.1 Terra (Max)Effort: max. Harness: OpenAI computer-use harness. | OpenAIReported by OpenAI | Oct 26, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 82.7% | GPT-6.1 Terra (Max)Effort: max. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 84.7% | GPT-6.1 Terra (Max)Effort: max. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 47.6%Hallucination rate 34.5% in the same run (lower is better) | GPT-6.1 Terra (Max)Effort: max. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry | Not yet published by OpenAI or any independent evaluator, checked Nov 2, 2026 | |||
| Instruction following | MultiChallengeAccuracy, Scale AI run. On Oct 28, 2026, Scale AI ranked it 6th, tied with Muse Spark Open. | 74.2%Plus or minus 5.4 points (95% interval) | GPT 6.1 TerraEffort: not published. Harness: none. | Scale AI SEAL | Oct 28, 2026 |
Price and speed
- GPT-6.1 Terra lists at $1 per million input tokens and $5 per million output tokens. For prompts under 272K tokens; $2 / $7.50 at 272K or more, as OpenRouter lists it. OpenAI pricing, Oct 26, 2026.
- GPT-6.1 Terra, at max effort, writes 97.2 output tokens per second on OpenAI's API, and its first token arrives 275 s after the request. Artificial Analysis, Nov 2, 2026.
- Fastest on the chart is the shortest time to a 500-token answer: time to first token plus 500 tokens at the median output speed.
Every model with a result, axis by axis
57 models. A maker's own figure and another lab's run are marked with their benchmark; a missing result reads "Not yet published", never zero.
| Model | Agentic coding | Code | Math | Science | Hard reasoning | Tool use | Computer use | Long context | Multimodal | Factuality | Answers in full | Instructions |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GPT-6.1 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-6 Sol | 44.4% | 57.6% | 89.8% | 94.3% | 47.9% | 61.6% | 64.4%Reported by OpenAIOSWorld 2.0 | 83.7% | 82.9% | 54.5% | 64% | Not yet published |
| ||||||||||||
| GPT-5.3-Codex | Not yet published | Not yet published | Not yet published | 91.5%Run by Artificial Analysis | 42.5% | Not yet published | Not yet published | 83.3% | 78.5% | Not yet published | Not yet published | 75.4%Run by Artificial AnalysisIFBench |
| ||||||||||||
| Claude Haiku 5.5 | 36.4% | 55% | 75.1% | 89.6% | 44.4% | 35.4% | 72.4%Reported by AnthropicOSWorld 2.1 | 82.7% | Not yet published | 34.7% | 78.8% | 67.7% |
| ||||||||||||
| 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 |
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| Kimi K3.1 Pro | 63.6% | 60.8% | Not yet published | 94.2%Reported by Moonshot AI | 52.5% | 73.3% | 79.6%Reported by Moonshot AIOSWorld 2.1 | 86.3% | 83.9% | 48.9% | Not yet published | Not yet published |
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| Kimi K3 | 17.2% | 59.5% | 72.2% | 93.1% | 46.9% | 58.3% | Not yet published | 88.7% | 80.5% | 50.6%Run by Epoch AISimpleQA Verified | 65.9% | Not yet published |
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| Kimi K2.7 Code | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 47.8% | 54% | 87.9% | 35% | 24.5% | Not yet published | 79.3% | Not yet published | 36.5%Run by Epoch AISimpleQA Verified | Not yet published | 63.1%Run by Artificial AnalysisIFBench |
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| Mistral Large 4 | 24.7%Run by Artificial AnalysisTerminal-Bench 4.0 | Not yet published | Not yet published | Not yet published | Not yet published | 57.8% | Not yet published | Not yet published | Not yet published | 26% | Not yet published | Not yet published |
| ||||||||||||
| Mistral Medium 3.5 | 0%Run by Artificial AnalysisTerminal-Bench 4.0 | 40.2% | Not yet published | 74.8%Run by Artificial AnalysisGPQA Diamond | 13.8% | 6.3% | Not yet published | 69.3% | 64.9% | 23% | 70.5% | 68.8%Run by Artificial AnalysisIFBench |
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| Grok 4.7 | 28.8% | 57.4% | 53% | 92.7% | 43.1% | 65.6% | Not yet published | 76.7% | Not yet published | 42.7% | 64.1% | Not yet published |
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| Grok 4.6 | 17.2% | 56.5% | 66% | 93.2% | 42.9% | 66.7% | Not yet published | 80.3% | Not yet published | 48.9%Run by Epoch AISimpleQA Verified | 83.6% | Not yet published |
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| Grok 4.5 | 8.6% | 55% | 57.2% | 93.4% | 42.7% | 57.9% | Not yet published | 79.3% | 80.4% | 48.3%Run by Epoch AISimpleQA Verified | 93.1% | Not yet published |
| ||||||||||||
| MiniMax M3.1 Flash | 25.3% | 53.4% | Not yet published | Not yet published | 48% | 72.5% | 61.7%Reported by MiniMaxOSWorld 2.0 | 79.7% | 79.1% | 45.1% | Not yet published | Not yet published |
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| Mercury 3 | 3% | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published |
| GLM-5.3-Flash | 37.4% | 51.6% | 55.8% | 90.2% | 39.9% | 60.4% | 59.1%Reported by Z.aiOSWorld 2.0 | 80% | 86%Run by Vals.aiMMMU-Pro | 28.2% | 65.4% | Not yet published |
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| GLM-5.3 | 38.9% | 59% | 68.8% | 90.9% | 42.3% | 62.2% | Not yet published | 79.7% | Not yet published | 32.3% | 71.5% | Not yet published |
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| GLM-5.2 | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 51.2% | 59.2% | Not yet published | 41.1% | 28.4% | Not yet published | 78.3% | Not yet published | 34.2%Run by Epoch AISimpleQA Verified | Not yet published | 73.3%Run by Artificial AnalysisIFBench |
| ||||||||||||
| Muse Spark Open | 6.6% | 58.4% | 69.8% | 88.6% | 43.9% | 49.7% | 80.4%Reported by MetaOSWorld-Verified | 78.3% | 80.9% | 42% | Not yet published | 74.2% |
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| Muse Wonder | 49.5% | 60.3% | 82.1% | Not yet published | 50.1% | 68.1% | 72.6%Reported by Meta | 80.7% | Not yet published | 38% | 42.7% | Not yet published |
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| Muse Spark 1.3 | 10.6% | 58.8% | 74% | 93.5%Run by Artificial AnalysisGPQA Diamond | 48.7% | 57.9% | 69.6% | 83% | 82% | 38% | 25.8% | Not yet published |
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| Llama 4 Scout | Not yet published | 21.3% | 7.8%Run by Epoch AIOTIS Mock AIME 2024-2025 | 51.8% | 3.8% | 0.2% | Not yet published | 27.7% | 52.9% | Not yet published | 70.1% | 39.5%Run by Artificial AnalysisIFBench |
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| Llama 4 Maverick | Not yet published | 31.7% | 20.6%Run by Epoch AIOTIS Mock AIME 2024-2025 | 67% | 4.9% | 0.2% | Not yet published | 50% | 62.1% | Not yet published | 58.3% | 43%Run by Artificial AnalysisIFBench |
| ||||||||||||
| Qwen3.8 27B | 5.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 46.6% | Not yet published | 90.5%Run by Artificial AnalysisGPQA Diamond | 33.9% | 48.2% | 84.3%Reported by AlibabaOSWorld-Verified | 82% | 76.3% | 17.3% | Not yet published | 79.5%Reported by AlibabaIFBench |
| ||||||||||||
| Qwen3.8 Max | 38.9% | 52.1% | 65.6% | 92.3% | 43.1% | 56.2% | Not yet published | 80.3% | 82.8% | 29.5% | 65.3% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Pro | 31.3% | 60.9% | Not yet published | Not yet published | 49.4% | 58.6% | 82%Reported by XiaomiOSWorld-Verified | 86.3% | Not yet published | 34.8% | 66.5% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Flash | 24.2% | 51.3% | Not yet published | Not yet published | 35.1% | 64.1% | 80.8%Reported by XiaomiOSWorld-Verified | 74.3% | 73.1% | 27.2% | 66.9% | Not yet published |
| ||||||||||||
| Ling 3.1 Flash | 32.8%Run by Artificial AnalysisTerminal-Bench 4.0 | 56.8% | Not yet published | Not yet published | 43.5% | 67.5% | Not yet published | 82.3% | Not yet published | 26.5% | Not yet published | Not yet published |
| ||||||||||||
| Step 5 Preview | 31.8% | 58.9% | Not yet published | 93.5%Reported by StepFunGPQA Diamond | 46.5% | 51% | Not yet published | 88.3% | 76.4% | 36.4% | 59.7% | Not yet published |
| ||||||||||||
Agentic codingTerminal-Bench 4.0
- Claude Opus 5.565.2%
- Claude Sonnet 5.564.1%
- Kimi K3.1 Pro63.6%
- GPT-6 Astra59.6%
- Claude Fable 5.158.1%
- Gemini 4 Argon57.6%
- GPT-6.1 Sol55.1%
- Claude Opus 553.5%
- GPT-6.1 Terra49.5%
- Muse Wonder49.5%
- GPT-6 Sol44.4%
- Claude Fable 541.4%
- GLM-5.338.9%
- Qwen3.8 Max38.9%
- GPT-5.6 Sol37.9%
- GLM-5.3-Flash37.4%
- Claude Haiku 5.536.4%
- DeepSeek V4.1 Flash31.8%
- Step 5 Preview31.8%
- MiMo-V2.6-Pro31.3%
- Grok 4.728.8%
- MiniMax M3.1 Flash25.3%
- MiMo-V2.6-Flash24.2%
- Claude Opus 4.823.2%
- GPT-5.6 Terra22.7%
- Gemini 3.8 Flash19.7%
- Kimi K317.2%
- Grok 4.617.2%
- DeepSeek V4 Pro14.1%
- GPT-6 Luna13.6%
- GPT-5.6 Luna11.6%
- Claude Sonnet 510.6%
- Muse Spark 1.310.6%
- Grok 4.58.6%
- Muse Spark Open6.6%
- Mercury 33%
- Gemini 3.1 Pro Preview2.5%
- Ling 3.1 Flash32.8%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Large 424.7%Artificial Analysis's run, Terminal-Bench 4.0
- GPT-5.514.6%Artificial Analysis's run, Terminal-Bench 4.0
- gpt-oss-120b14.2%Terminal-Bench's run, Terminal-Bench 2.0
- Gemini 3.6 Flash7.1%Artificial Analysis's run, Terminal-Bench 4.0
- Qwen3.8 27B5.6%Artificial Analysis's run, Terminal-Bench 4.0
- Claude Sonnet 4.63%Artificial Analysis's run, Terminal-Bench 4.0
- Kimi K2.7 Code1%Artificial Analysis's run, Terminal-Bench 4.0
- GLM-5.21%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Medium 3.50%Artificial Analysis's run, Terminal-Bench 4.0
The other models in the grid have no result on Terminal-Bench 4.0 yet.
CodeSciCode
- Claude Opus 5.566.9%
- Claude Fable 5.163.1%
- Gemini 4 Argon61.8%
- Claude Sonnet 5.561%
- Claude Fable 561%
- MiMo-V2.6-Pro60.9%
- Kimi K3.1 Pro60.8%
- Muse Wonder60.3%
- Kimi K359.5%
- GLM-5.359%
- Step 5 Preview58.9%
- Muse Spark 1.358.8%
- Gemini 3.1 Pro Preview58.7%
- Muse Spark Open58.4%
- GPT-6 Sol57.6%
- Grok 4.757.4%
- GPT-5.6 Sol57.1%
- Ling 3.1 Flash56.8%
- Gemini 3.8 Flash56.6%
- GPT-6 Astra56.5%
- Grok 4.656.5%
- Claude Opus 556.4%
- DeepSeek V4.1 Flash55.9%
- GPT-5.555.8%
- GPT-6.1 Terra55.1%
- GPT-5.6 Terra55%
- Claude Haiku 5.555%
- Grok 4.555%
- GPT-6 Luna54.6%
- Claude Opus 4.754.5%
- Claude Opus 4.854.4%
- Claude Sonnet 554.3%
- GPT-6.1 Sol54.2%
- GPT-5.6 Luna53.6%
- Gemini 3.6 Flash53.4%
- MiniMax M3.1 Flash53.4%
- Qwen3.8 Max52.1%
- GLM-5.3-Flash51.6%
- MiMo-V2.6-Flash51.3%
- GLM-5.251.2%
- DeepSeek V4 Pro51%
- Claude Sonnet 4.650.1%
- Kimi K2.7 Code47.8%
- Qwen3.8 27B46.6%
- Claude Sonnet 4.545.7%
- Gemma 4 31B45.5%
- Claude Haiku 4.542.2%
- Mistral Medium 3.540.2%
- gpt-oss-120b34%
- Llama 4 Maverick31.7%
- Llama 4 Scout21.3%
The other models in the grid have no result on SciCode yet.
MathFrontierMath Tiers 1-3
- GPT-6.1 Sol93.7%
- GPT-6 Astra93.7%
- Claude Opus 5.591.2%
- GPT-6.1 Terra90.9%
- Claude Fable 5.190.2%
- GPT-6 Sol89.8%
- GPT-5.6 Sol89.1%
- Claude Sonnet 5.588.8%
- Claude Fable 587%
- GPT-5.6 Terra86%
- Gemini 4 Argon86%
- Claude Opus 585.6%
- GPT-5.585.3%
- GPT-5.6 Luna82.1%
- Muse Wonder82.1%
- Claude Opus 4.880%
- GPT-6 Luna78.9%
- GPT-5.478.6%
- Claude Haiku 5.575.1%
- Muse Spark 1.374%
- Kimi K372.2%
- DeepSeek V4.1 Flash71.2%
- Claude Opus 4.770.2%
- Muse Spark Open69.8%
- GLM-5.368.8%
- Gemini 3.8 Flash68.4%
- Claude Opus 4.666%
- Grok 4.666%
- Claude Sonnet 565.6%
- Qwen3.8 Max65.6%
- DeepSeek V4 Pro64.6%
- Gemini 3.1 Pro Preview59.6%
- GLM-5.259.2%
- Gemini 3.6 Flash58.9%
- Grok 4.557.2%
- GLM-5.3-Flash55.8%
- Kimi K2.7 Code54%
- Grok 4.753%
- Claude Opus 4.534.4%
- Claude Sonnet 4.523.9%
- gpt-oss-120b88.9%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Sonnet 4.671.1%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Haiku 4.566.7%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Maverick20.6%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Scout7.8%Epoch AI's run, OTIS Mock AIME 2024-2025
The other models in the grid have no result on FrontierMath Tiers 1-3 yet.
ScienceGPQA Diamond
- Gemini 4 Argon96.4%
- GPT-6 Astra95.8%
- Claude Sonnet 5.595.6%
- GPT-6.1 Sol95.4%
- Gemini 3.8 Flash95.4%
- Gemini 3.1 Pro Preview94.4%
- GPT-6.1 Terra94.3%
- GPT-6 Sol94.3%
- Gemini 3.6 Flash94.1%
- Claude Opus 593.9%
- GPT-5.6 Sol93.5%
- Grok 4.593.4%
- GPT-5.6 Terra93.3%
- GPT-5.493.3%
- DeepSeek V4.1 Flash93.2%
- Grok 4.693.2%
- Kimi K393.1%
- Grok 4.792.7%
- Qwen3.8 Max92.3%
- DeepSeek V4 Pro91.7%
- GPT-5.6 Luna91.6%
- Claude Opus 4.891%
- GLM-5.390.9%
- Claude Opus 5.590.6%
- GPT-6 Luna90.5%
- GLM-5.3-Flash90.2%
- Claude Haiku 5.589.6%
- Muse Spark Open88.6%
- Claude Opus 4.688.4%
- Kimi K2.7 Code87.9%
- Claude Opus 4.786.4%
- Claude Opus 4.586%
- Claude Fable 585.9%
- Claude Sonnet 4.582.3%
- Claude Sonnet 580.3%
- Claude Sonnet 4.678.8%
- gpt-oss-120b75.8%
- Claude Haiku 4.571.2%
- Llama 4 Maverick67%
- Llama 4 Scout51.8%
- Kimi K3.1 Pro94.2%Moonshot AI's own figure
- GPT-5.593.5%Artificial Analysis's run
- Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
- Step 5 Preview93.5%StepFun's own figure, GPQA Diamond
- Claude Fable 5.193.4%Vals.ai's run
- GPT-5.3-Codex91.5%Artificial Analysis's run
- Qwen3.8 27B90.5%Artificial Analysis's run, GPQA Diamond
- Gemma 4 31B85.7%Artificial Analysis's run, GPQA Diamond
- Mistral Medium 3.574.8%Artificial Analysis's run, GPQA Diamond
The other models in the grid have no result on GPQA Diamond yet.
Hard reasoningHumanity's Last Exam
- Claude Opus 5.561.4%
- Claude Fable 5.159.1%
- Gemini 4 Argon57.1%
- Claude Fable 555.5%
- Claude Sonnet 5.555%
- Claude Opus 554.9%
- GPT-6 Astra54.7%
- GPT-6.1 Sol52.9%
- Kimi K3.1 Pro52.5%
- Muse Wonder50.1%
- GPT-5.6 Sol49.5%
- MiMo-V2.6-Pro49.4%
- Claude Opus 4.848.7%
- Muse Spark 1.348.7%
- MiniMax M3.1 Flash48%
- GPT-6 Sol47.9%
- Gemini 3.8 Flash47.8%
- Gemini 3.1 Pro Preview47%
- Kimi K346.9%
- Step 5 Preview46.5%
- GPT-6.1 Terra46.2%
- GPT-5.545.8%
- Claude Haiku 5.544.4%
- Muse Spark Open43.9%
- GPT-5.443.7%
- Ling 3.1 Flash43.5%
- DeepSeek V4.1 Flash43.3%
- Grok 4.743.1%
- Qwen3.8 Max43.1%
- GPT-5.6 Terra42.9%
- Grok 4.642.9%
- Grok 4.542.7%
- GPT-5.3-Codex42.5%
- Claude Opus 4.742.3%
- GLM-5.342.3%
- Claude Sonnet 541.3%
- GLM-5.241.1%
- DeepSeek V4 Pro41%
- Gemini 3.6 Flash40.8%
- Claude Opus 4.639.9%
- GLM-5.3-Flash39.9%
- GPT-5.6 Luna39.5%
- GPT-6 Luna38.5%
- MiMo-V2.6-Flash35.1%
- Kimi K2.7 Code35%
- Qwen3.8 27B33.9%
- Claude Sonnet 4.633.6%
- Claude Opus 4.530.1%
- Gemma 4 31B23.6%
- gpt-oss-120b19.6%
- Claude Sonnet 4.517.8%
- Mistral Medium 3.513.8%
- Claude Haiku 4.510.4%
- Llama 4 Maverick4.9%
- Llama 4 Scout3.8%
The other models in the grid have no result on Humanity's Last Exam yet.
Tool useAutomationBench-AA
- Gemini 4 Argon77.5%
- Kimi K3.1 Pro73.3%
- MiniMax M3.1 Flash72.5%
- Claude Sonnet 5.571.8%
- Claude Opus 5.569.5%
- GPT-6 Astra68.5%
- Muse Wonder68.1%
- Ling 3.1 Flash67.5%
- Grok 4.666.7%
- DeepSeek V4.1 Flash66.6%
- Grok 4.765.6%
- GPT-6.1 Sol64.9%
- MiMo-V2.6-Flash64.1%
- GLM-5.362.2%
- GPT-6 Sol61.6%
- GLM-5.3-Flash60.4%
- GPT-6.1 Terra60.2%
- GPT-5.6 Sol60.1%
- Gemini 3.8 Flash59.9%
- GPT-5.6 Terra59.6%
- Claude Fable 5.159.4%
- MiMo-V2.6-Pro58.6%
- Kimi K358.3%
- Grok 4.557.9%
- Muse Spark 1.357.9%
- Mistral Large 457.8%
- DeepSeek V4 Pro56.7%
- Claude Opus 556.6%
- Qwen3.8 Max56.2%
- Claude Fable 554.1%
- GPT-6 Luna53.2%
- Gemini 3.6 Flash53%
- Step 5 Preview51%
- GPT-5.6 Luna50.2%
- Muse Spark Open49.7%
- Qwen3.8 27B48.2%
- GPT-5.547.3%
- Claude Opus 4.845.6%
- Claude Sonnet 536.5%
- Claude Haiku 5.535.4%
- Gemini 3.1 Pro Preview35.4%
- GLM-5.228.4%
- Kimi K2.7 Code24.5%
- Claude Sonnet 4.620.1%
- Claude Sonnet 4.514.1%
- Mistral Medium 3.56.3%
- Gemma 4 31B4.9%
- Claude Haiku 4.53.2%
- gpt-oss-120b0.2%
- Llama 4 Scout0.2%
- Llama 4 Maverick0.2%
The other models in the grid have no result on AutomationBench-AA yet.
Computer useOSWorld 2.1
- Claude Opus 577.7%
- Muse Spark 1.369.6%
- Qwen3.8 27B84.3%Alibaba's own figure, OSWorld-Verified
- Gemini 3.6 Flash83%Google's own figure, OSWorld-Verified
- MiMo-V2.6-Pro82%Xiaomi's own figure, OSWorld-Verified
- Claude Opus 5.581.8%Anthropic's own figure
- MiMo-V2.6-Flash80.8%Xiaomi's own figure, OSWorld-Verified
- Claude Fable 5.180.7%Anthropic's own figure
- Muse Spark Open80.4%Meta's own figure, OSWorld-Verified
- Claude Sonnet 5.580.1%Anthropic's own figure
- Kimi K3.1 Pro79.6%Moonshot AI's own figure, OSWorld 2.1
- GPT-6.1 Sol78%OpenAI's own figure, OSWorld 2.1
- GPT-6 Astra75.8%Meta's run
- GPT-6.1 Terra74.2%OpenAI's own figure, OSWorld 2.1
- Muse Wonder72.6%Meta's own figure
- Claude Haiku 5.572.4%Anthropic's own figure, OSWorld 2.1
- DeepSeek V4.1 Flash69.3%Moonshot AI's run, OSWorld 2.1
- Gemini 4 Argon69.2%Google's own figure, OSWorld 2.0
- GPT-6 Sol64.4%OpenAI's own figure, OSWorld 2.0
- GPT-5.6 Sol62.7%OSWorld team's run, OSWorld 2.0
- MiniMax M3.1 Flash61.7%MiniMax's own figure, OSWorld 2.0
- GLM-5.3-Flash59.1%Z.ai's own figure, OSWorld 2.0
- Gemini 3.8 Flash59%Google's own figure, OSWorld 2.0
- Claude Sonnet 557%Anthropic's own figure
- Claude Opus 4.854.8%OSWorld team's run, OSWorld 2.0
- GPT-5.549.5%OSWorld team's run, OSWorld 2.0
- GPT-6 Luna48.9%Anthropic's run, OSWorld 2.1
- Claude Opus 4.748.9%OSWorld team's run, OSWorld 2.0
- Claude Sonnet 4.641.5%OSWorld team's run, OSWorld 2.0
The other models in the grid have no result on OSWorld 2.1 yet.
Long contextAA-LCR v1.1
- Kimi K388.7%
- Step 5 Preview88.3%
- Kimi K3.1 Pro86.3%
- MiMo-V2.6-Pro86.3%
- Claude Fable 5.185.3%
- Claude Opus 5.584.7%
- GPT-5.584.3%
- GPT-5.6 Sol84%
- GPT-5.6 Luna83.7%
- GPT-6 Sol83.7%
- GPT-6 Luna83.3%
- GPT-5.3-Codex83.3%
- GPT-6.1 Sol83%
- GPT-5.6 Terra83%
- Muse Spark 1.383%
- GPT-6.1 Terra82.7%
- Claude Haiku 5.582.7%
- Claude Sonnet 5.582.7%
- DeepSeek V4.1 Flash82.7%
- Claude Fable 582.3%
- Ling 3.1 Flash82.3%
- GPT-5.482%
- Claude Sonnet 582%
- Gemini 3.1 Pro Preview82%
- Qwen3.8 27B82%
- Gemini 3.8 Flash81.3%
- GPT-6 Astra80.7%
- Muse Wonder80.7%
- DeepSeek V4 Pro80.3%
- Grok 4.680.3%
- Qwen3.8 Max80.3%
- Claude Sonnet 4.680%
- Gemini 3.6 Flash80%
- GLM-5.3-Flash80%
- Gemini 4 Argon79.7%
- MiniMax M3.1 Flash79.7%
- GLM-5.379.7%
- Claude Opus 579.3%
- Kimi K2.7 Code79.3%
- Grok 4.579.3%
- Claude Opus 4.778.7%
- GLM-5.278.3%
- Muse Spark Open78.3%
- Claude Opus 4.678%
- Claude Opus 4.877.7%
- Claude Opus 4.577.3%
- Grok 4.776.7%
- Claude Haiku 4.574.3%
- MiMo-V2.6-Flash74.3%
- Claude Sonnet 4.572.3%
- Gemma 4 31B69.7%
- Mistral Medium 3.569.3%
- gpt-oss-120b52%
- Llama 4 Maverick50%
- Llama 4 Scout27.7%
The other models in the grid have no result on AA-LCR v1.1 yet.
MultimodalMMMU-Pro
- Claude Opus 5.587.7%
- GPT-6 Astra86.9%
- GPT-6.1 Sol86%
- Gemini 3.8 Flash85.6%
- GPT-6.1 Terra84.7%
- Claude Opus 584.7%
- Kimi K3.1 Pro83.9%
- GPT-5.6 Sol83.4%
- Gemini 3.6 Flash83.2%
- GPT-6 Sol82.9%
- Qwen3.8 Max82.8%
- Gemini 3.1 Pro Preview82.4%
- Muse Spark 1.382%
- Muse Spark Open80.9%
- GPT-5.6 Terra80.7%
- DeepSeek V4.1 Flash80.6%
- Kimi K380.5%
- Grok 4.580.4%
- GPT-5.579.9%
- GPT-6 Luna79.7%
- MiniMax M3.1 Flash79.1%
- Claude Opus 4.778.8%
- GPT-5.6 Luna78.6%
- GPT-5.3-Codex78.5%
- GPT-5.478.4%
- Claude Sonnet 577.3%
- Step 5 Preview76.4%
- Qwen3.8 27B76.3%
- Claude Opus 4.675.4%
- Claude Opus 4.574%
- Gemma 4 31B73.4%
- Claude Sonnet 4.673.3%
- MiMo-V2.6-Flash73.1%
- Claude Sonnet 4.568.7%
- Mistral Medium 3.564.9%
- Llama 4 Maverick62.1%
- Claude Haiku 4.558.6%
- Llama 4 Scout52.9%
- Claude Fable 5.186.3%Moonshot AI's run
- GLM-5.3-Flash86%Vals.ai's run, MMMU-Pro
The other models in the grid have no result on MMMU-Pro yet.
FactualityAA-Omniscience Accuracy
- Claude Fable 5.168.4%
- Claude Opus 5.565.5%
- Claude Fable 565.4%
- GPT-6.1 Sol61.8%
- GPT-6 Astra61.6%
- Claude Opus 560.9%
- Gemini 3.1 Pro Preview54.9%
- GPT-6 Sol54.5%
- Claude Sonnet 5.551.5%
- Gemini 3.8 Flash50.5%
- Claude Opus 4.748.9%
- Kimi K3.1 Pro48.9%
- Claude Opus 4.848.8%
- Gemini 4 Argon48.3%
- GPT-6.1 Terra47.6%
- Claude Opus 4.647%
- Claude Opus 4.546.6%
- DeepSeek V4 Pro45.2%
- MiniMax M3.1 Flash45.1%
- Grok 4.742.7%
- GPT-5.6 Terra42.3%
- Muse Spark Open42%
- Claude Sonnet 4.640.9%
- Claude Sonnet 540.1%
- GPT-6 Luna39.6%
- DeepSeek V4.1 Flash39.6%
- Muse Wonder38%
- Muse Spark 1.338%
- Step 5 Preview36.4%
- MiMo-V2.6-Pro34.8%
- Claude Haiku 5.534.7%
- Claude Sonnet 4.532.9%
- GLM-5.332.3%
- Qwen3.8 Max29.5%
- GLM-5.3-Flash28.2%
- MiMo-V2.6-Flash27.2%
- Ling 3.1 Flash26.5%
- Mistral Large 426%
- Mistral Medium 3.523%
- Claude Haiku 4.518%
- Qwen3.8 27B17.3%
- GPT-5.6 Sol69.7%Epoch AI's run, SimpleQA Verified
- Gemini 3.6 Flash66.2%Epoch AI's run, SimpleQA Verified
- GPT-5.563%Epoch AI's run, SimpleQA Verified
- Kimi K350.6%Epoch AI's run, SimpleQA Verified
- Grok 4.648.9%Epoch AI's run, SimpleQA Verified
- Grok 4.548.3%Epoch AI's run, SimpleQA Verified
- GPT-5.6 Luna41%Epoch AI's run, SimpleQA Verified
- Kimi K2.7 Code36.5%Epoch AI's run, SimpleQA Verified
- GLM-5.234.2%Epoch AI's run, SimpleQA Verified
- gpt-oss-120b16.8%OpenAI's own figure, SimpleQA
- Gemma 4 31B10.4%Epoch AI's run, SimpleQA Verified
The other models in the grid have no result on AA-Omniscience Accuracy yet.
Answers in fullSpeechMap
- Grok 4.593.1%
- Gemini 3.6 Flash87.2%
- Gemini 4 Argon87%
- Gemini 3.8 Flash86.1%
- Grok 4.683.6%
- Claude Opus 5.582.8%
- Gemma 4 31B82.3%
- Claude Sonnet 5.581.6%
- Claude Haiku 5.578.8%
- Claude Opus 573.7%
- Claude Fable 5.172.4%
- DeepSeek V4 Pro72%
- GLM-5.371.5%
- Mistral Medium 3.570.5%
- Claude Opus 4.770.2%
- Llama 4 Scout70.1%
- GPT-6.1 Sol69.5%
- GPT-6 Astra68.2%
- Claude Opus 4.867.4%
- MiMo-V2.6-Flash66.9%
- MiMo-V2.6-Pro66.5%
- Kimi K365.9%
- GLM-5.3-Flash65.4%
- Qwen3.8 Max65.3%
- Claude Fable 564.8%
- Grok 4.764.1%
- GPT-6 Sol64%
- GPT-6 Luna63.4%
- Claude Opus 4.659.9%
- Gemini 3.1 Pro Preview59.9%
- Step 5 Preview59.7%
- Llama 4 Maverick58.3%
- Claude Opus 4.557.5%
- Muse Wonder42.7%
- gpt-oss-120b36.3%
- Claude Sonnet 4.635.8%
- Claude Sonnet 4.531.4%
- Muse Spark 1.325.8%
- Claude Haiku 4.524.7%
The other models in the grid have no result on SpeechMap yet.
Instruction followingMultiChallenge
- GPT-6.1 Sol82%
- Gemini 4 Argon78.7%
- DeepSeek V4.1 Flash74.9%
- GPT-6.1 Terra74.2%
- Muse Spark Open74.2%
- Gemini 3.1 Pro Preview71.4%
- Claude Haiku 5.567.7%
- Claude Opus 4.559%
- Claude Sonnet 4.555.3%
- Claude Haiku 4.550.5%
- gpt-oss-120b45.3%
- Claude Opus 4.637.2%
- Qwen3.8 27B79.5%Alibaba's own figure, IFBench
- GPT-5.575.9%Artificial Analysis's run, IFBench
- Gemma 4 31B75.6%Artificial Analysis's run, IFBench
- GPT-5.3-Codex75.4%Artificial Analysis's run, IFBench
- GPT-5.473.9%Artificial Analysis's run, IFBench
- GLM-5.273.3%Artificial Analysis's run, IFBench
- GPT-5.6 Sol72.7%Artificial Analysis's run, IFBench
- GPT-5.6 Terra71.2%Artificial Analysis's run, IFBench
- Mistral Medium 3.568.8%Artificial Analysis's run, IFBench
- Claude Fable 563.5%Artificial Analysis's run, IFBench
- Kimi K2.7 Code63.1%Artificial Analysis's run, IFBench
- Claude Opus 4.862.2%Artificial Analysis's run, IFBench
- Claude Opus 4.758.6%Artificial Analysis's run, IFBench
- Claude Sonnet 4.656.6%Artificial Analysis's run, IFBench
- Llama 4 Maverick43%Artificial Analysis's run, IFBench
- Llama 4 Scout39.5%Artificial Analysis's run, IFBench
The other models in the grid have no result on MultiChallenge yet.
Every measure on record
Cost, speed, reliability, knowledge-work and domain results for GPT-6.1 Terra beyond the twelve chart axes, each with the run it comes from and its publisher. These stay separate measures; none is folded into the chart.
| Measure | GPT-6.1 Terra | 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. | 7 of 19 | GILD route matrix | Oct 29, 2026 | |
| Cost | ||||
| Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded. | 10,204 | GPT-6.1 Terra (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. | $0.11 | GPT-6.1 Terra (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. | $0.092 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task. | $0.23 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task. | $0.18 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task. | $0.12 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Cost per taskLower is better. What one Intelligence Index task cost AA at list price, input, cache, output and reasoning tokens together. | $0.96 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 28, 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. | $972.34 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 28, 2026 |
| Output tokens per taskLower is better. Tokens the model wrote per Intelligence Index task, reasoning included: how verbose it is. | 35,096 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 24,892 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Cached inputLower is better. The maker's list price for input read from its prompt cache, per million tokens. | $0.05 | OpenAI | Oct 28, 2026 | |
| Speed | ||||
| End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt. | 224 s | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 83 s | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Time to first answer token, 100K promptLower is better. Median seconds to the first answer token with a 100,000-token prompt. | 218 s | GPT-6.1 Terra (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. | 78 s | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long. | 91 tokens/s | GPT-6.1 Terra (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. | 91 tokens/s | GPT-6.1 Terra (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. | 384 s | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Time to first token, 100K promptLower is better. Median seconds to the first chunk when the prompt is about 100,000 tokens long: long-input latency, separate from window size. | 218 s | GPT-6.1 Terra (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. | 78 s | GPT-6.1 Terra (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. | 34.5% | Max effort | Artificial Analysis | Nov 2, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 47.6% | Max effort | Artificial Analysis | Nov 2, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 29.8 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,402 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 28.6% | GPT-6.1 Terra (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. | 1,476 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 82.7% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 28% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks. | 36.0% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 46.2% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 51 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 28, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 84.7% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| SciCode (AA run)SciCode subproblem accuracy in AA's run. | 55.1% | GPT-6.1 Terra (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. | 55.6% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness. | 57.6% | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 53.6 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 49.1 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 47.1 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 49 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 49.5 | GPT-6.1 Terra (Max) | Artificial Analysis | Oct 27, 2026 |
Routes, prices and uptime
Where GPT-6.1 Terra is offered, what each route charges, and how each endpoint is holding up.
Where it is offered
7 of 19 routes GILD tracks offer GPT-6.1 Terra today, preview included. Read Oct 29, 2026 from each route's own pages.
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Amazon Bedrock | Available | openai.gpt-6.1-terraus.openai.gpt-6.1-terraglobal.openai.gpt-6.1-terra | In-Region on bedrock-mantle, us./global. profiles on bedrock-runtime; 1,050,000 context, 128,000 output; Priority and Flex not supported | Amazon Web Services |
| Codex | Available | gpt-6.1-terra | codex -m gpt-6.1-terra; needs Codex CLI 0.159.0 or later; listed for the desktop app, ChatGPT Work and Codex CLI; the IDE extension isn't listed | OpenAI |
| Databricks | Available | databricks-gpt-6-1-terra | Model service name system.ai.gpt-6-1-terra; listed on the supported-models page | Databricks |
| The maker's own API | Available | gpt-6.1-terra | 1,050,000 context, 128,000 output; paid tiers Build to Grow only, with no free tier | OpenAI |
| GitHub Copilot | Available | not statedpicker label GPT-6.1 Terra | available (GA) | GitHub |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub |
| Microsoft Foundry | Available | gpt-6.1-terra | Version 2026-10-26; 1,050,000 context (input 922,000, output 128,000) | Microsoft |
| OpenRouter | Available | openai/gpt-6.1-terraopenai/gpt-6.1-terra:batch | 1,050,000 context for the model; top provider 128,000 output; batch variant listed | OpenRouter |
Not offered on 8 routes: Antigravity, Claude on Google Cloud (Anthropic managed), Claude Platform on AWS, Cursor, Google Cloud Vertex / Agent Platform (Google managed), OpenCode, Snowflake Cortex and Windsurf / Devin.
3 routes do not say: Claude Code, Gemini CLI and Grok Build.
What each of these 11 routes' pages say, with sources
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Antigravity | Not offered | Antigravity lists Gemini, Claude and GPT-OSS models only | ||
| Claude on Google Cloud (Anthropic managed) | Not offered | Takes the Claude API's model IDs, which name Anthropic's Claude models only | Anthropic, Claude Models on Google Cloud (Anthropic managed)Anthropic, Models overview | |
| Claude Platform on AWS | Not offered | Claude Platform on AWS lists Anthropic's Claude models only | Anthropic | |
| Cursor | Not offered | Cursor's OpenAI rows stop at GPT-5.6 Sol, Terra, Luna | Cursor | |
| Google Cloud Vertex / Agent Platform (Google managed) | Not offered | OpenAI section lists gpt-oss only | Google Cloud, Gemini Enterprise Agent Platform partner models for MaaSGoogle Cloud, Anthropic's Claude on Google Cloud models | |
| OpenCode | Not offered | OpenCode Zen lists GPT 6.1 Sol and GPT 5.6 Terra; GPT-6.1 Terra isn't among them, and Go lists neither model | OpenCode, ModelsOpenCode, Go | |
| Snowflake Cortex | Not offered | Cortex lists GPT-6.1 Sol and GPT-5.6 Terra; GPT-6.1 Terra isn't among them | Snowflake | |
| Windsurf / Devin | Not offered | Devin lists GPT-6.1 Sol and GPT-5.6 Terra; GPT-6.1 Terra isn't among them | Cognition | |
| Claude Code | Not stated | No vendor documents this model in Claude Code, which takes Anthropic model names or a cloud provider's Claude IDs | Anthropic | |
| Gemini CLI | Not stated | Gemini CLI's model page names Gemini models only | ||
| 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 $1 / $5 per million input and output tokens. US dollars per million tokens, as each route lists them, one row per route and rate plan, cheapest standard rate first after the maker's own; a blended rate states its mix. OpenRouter's endpoints follow under one heading, each with its monitor's uptime over 1 day and 30 minutes and the context and output it serves.
| Route | Standard, in / out | Cache read | Other rates | Source, or uptime (1 day / 30 min) and limits |
|---|---|---|---|---|
| OpenAI APIMakerLowest | $1 / $5 | $0.05 | Cache write $1.25 | OpenAI, Oct 26, 2026OpenAI, Oct 28, 2026 |
| Artificial Analysis price record | $1 / $5 | $0.05 | Blended $2, 3 input : 1 output, no cacheBlended $0.73, 7 cache-hit : 2 input : 1 outputCache write $1.25 | Artificial Analysis, Oct 27, 2026 |
| OpenRouterprompts under 272K tokens | $1 / $5 | $0.05 | Cache read $0.1, prompts of 272K tokens or moreCache write $2.50, 5-minute cache, prompts of 272K tokens or moreCache write $1.25, 5-minute cache, prompts under 272K tokensLong context $2 / $7.50, prompts of 272K tokens or more | OpenRouter, Oct 29, 2026 |
| Through OpenRouter, 4 provider endpoints. OpenRouter, Oct 29, 2026 | ||||
| OpenAIprompts under 272K tokens | $1 / $5 | $0.05 | Cache read $0.1, prompts of 272K tokens or moreCache write $2.50, 5-minute cache, prompts of 272K tokens or moreCache write $1.25, 5-minute cache, prompts under 272K tokensLong context $2 / $7.50, prompts of 272K tokens or more | Up 100% / 100%1.05M context, 128K output |
| Azure (eu)prompts under 272K tokens | $1.20 / $6 | $0.06 | Cache read $0.12, prompts of 272K tokens or moreCache write $3, 5-minute cache, prompts of 272K tokens or moreCache write $1.50, 5-minute cache, prompts under 272K tokensLong context $2.40 / $9, prompts of 272K tokens or more | Up 100% / 100%1.05M context, 128K output |
| OpenAI (fast, priority) | Cache read $0.2, priority tier, prompts of 272K tokens or moreCache read $0.1, priority tier, prompts under 272K tokensCache write $5, priority tier, 5-minute cache, prompts of 272K tokens or moreCache write $2.50, priority tier, 5-minute cache, prompts under 272K tokensLong context $4 / $15, priority tier, prompts of 272K tokens or morePriority $2 / $10, priority tier, prompts under 272K tokens | Up 100% / 100%1.05M context, 128K output | ||
| OpenAI (flex) | Cache read $0.05, flex tier, prompts of 272K tokens or moreCache read $0.025, flex tier, prompts under 272K tokensCache write $1.25, flex tier, 5-minute cache, prompts of 272K tokens or moreCache write $0.63, flex tier, 5-minute cache, prompts under 272K tokensFlex $0.5 / $2.50, flex tier, prompts under 272K tokensLong context $1 / $3.75, flex tier, prompts of 272K tokens or more | Up 95.7% / 100%1.05M context, 128K output | ||
Lineup
OpenAI's 12 releases in 7 families, oldest to newest along each tier, with list price and speed. GPT-6.1 Terra 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
- 5.6Current. In 5 products we coverPrice$2 / $12Speed111.1 tok/s
- This page6.1Current. In 4 products we coverPrice$1 / $5Speed97.2 tok/s
GPT Sol
OpenAI's GPT model tier for demanding everyday and agentic work.
3 releases
GPT Luna
OpenAI's most efficient GPT model tier for focused, high-volume tasks.
2 releases
GPT Astra
OpenAI's highest-capability GPT model tier.
1 release
GPT-5
OpenAI's GPT-5 frontier models, released before the Sol, Terra and Luna tiers.
2 releases
gpt-oss
OpenAI's open-weight GPT models under the Apache 2.0 license.
1 release
GPT Codex
OpenAI's GPT models tuned for agentic coding in Codex.
1 release
Where it fits
The layers of Agentic Software Development that GPT-6.1 Terra can power. A product supplies the rest.
Product & Engineering, Software Development
Agentic Software Development
- Primary role
- Foundation Model / Reasoning Engine
GPT-6.1 Terra can power coding, reasoning, and validation work inside an agentic software-development product. The Model does not itself provide the surrounding interface, execution environment, or system of record.
- Supporting
Work planning & task decomposition
The Model can assist with work planning & task decomposition when a Product supplies the necessary context and tools.
- Supporting
Codebase context & intelligence
The Model can assist with codebase context & intelligence when a Product supplies the necessary context and tools.
- Supporting
Coding & implementation
The Model can assist with coding & implementation when a Product supplies the necessary context and tools.
- Supporting
Debugging & investigation
The Model can assist with debugging & investigation when a Product supplies the necessary context and tools.
- Supporting
Testing & verification
The Model can assist with testing & verification when a Product supplies the necessary context and tools.
- Supporting
Code review & quality
The Model can assist with code review & quality when a Product supplies the necessary context and tools.
Products
We cover 4 products that offer GPT-6.1 Terra today: 3 subscriptions and 1 API.
Through a subscription
Through an API
Limits each vendor states
- GitHub CopilotCopilot Pro, Copilot 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, Business, Enterprise, Edu
- 35-285 local messages per five-hour period on Plus and Standard Business (estimate); Pro plans currently have no five-hour limit; Work and Codex only, not Chat; Enterprise access also depends on workspace availability and administrator controls
- CodexPlus, Pro, Business, Enterprise, Edu
- 35-285 local messages per five-hour period on Plus and Standard Business (estimate); Pro plans currently have no five-hour limit; Work and Codex only, not Chat; Enterprise access also depends on workspace availability and administrator controls
Plan access as each vendor's page states it: GitHub (Oct 31, 2026), OpenAI (Oct 28, 2026).
Comparisons
GILD comparisons that name GPT-6.1 Terra, then those of the clouds and APIs that serve it.
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Names GPT-6.1 Terra
- OpenAI API vs Azure OpenAI: Same Models, Different ContractsNames GPT-6.1 Terra
- OpenAI API vs Gemini API: Who Finishes the Task for Less?Names GPT-6.1 Terra
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve GPT-6.1 Terra
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve GPT-6.1 Terra
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Compares routes that serve GPT-6.1 Terra
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve GPT-6.1 Terra
What practitioners report
Strongest on Speed, weakest on Quality and reasoning.
Each figure is the share of accounts naming GPT-6.1 Terra 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. | 33% | 3 favorable, 6 not, 8 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 40% | 2 favorable, 3 not, 5 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | Only concerns on record | 0 favorable, 1 not, 1 author |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | Only concerns on record | 0 favorable, 2 not, 2 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 80% | 8 favorable, 2 not, 9 authors |
| SpeedResponse time, time to first token, and throughput. | 83% | 5 favorable, 1 not, 5 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | Only concerns on record | 0 favorable, 1 not, 1 author |
Every model on these seven axes
| Axis | 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-6 Sol | GPT-5.3-Codex | Claude Haiku 5.5 | Claude Sonnet 5.5 | Claude Opus 5.5 | Claude Fable 5.1 | Claude Opus 5 | Claude Sonnet 5 | Claude Fable 5 | Claude Opus 4.8 | Claude Opus 4.7 | Claude Sonnet 4.6 | Claude Opus 4.6 | Claude Opus 4.5 | Claude Haiku 4.5 | Claude Sonnet 4.5 | Gemini 4 Argon | Gemini 3.8 Flash | Gemma 4 31B | Gemini 3.1 Pro Preview | Gemini 3.6 Flash | DeepSeek V4.1 Flash | DeepSeek V4 Pro | Kimi K3.1 Pro | Kimi K3 | Kimi K2.7 Code | Mistral Large 4 | Mistral Medium 3.5 | Grok 4.7 | Grok 4.6 | Grok 4.5 | MiniMax M3.1 Flash | Mercury 3 | GLM-5.3-Flash | GLM-5.3 | GLM-5.2 | Muse Spark Open | Muse Wonder | Muse Spark 1.3 | Llama 4 Scout | Llama 4 Maverick | Qwen3.8 27B | Qwen3.8 Max | MiMo-V2.6-Pro | MiMo-V2.6-Flash | Ling 3.1 Flash | Step 5 Preview |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Quality and reasoning | 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 | 31%10 favorable, 22 not, 32 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 73%19 favorable, 7 not, 26 authors | 64%14 favorable, 8 not, 22 authors | 68%17 favorable, 8 not, 25 authors | 54%15 favorable, 13 not, 28 authors | 50%6 favorable, 6 not, 12 authors | 56%9 favorable, 7 not, 16 authors | 68%13 favorable, 6 not, 18 authors | 68%17 favorable, 8 not, 25 authors | 57%12 favorable, 9 not, 21 authors | 67%12 favorable, 6 not, 18 authors | 70%19 favorable, 8 not, 27 authors | 62%13 favorable, 8 not, 20 authors | 58%14 favorable, 10 not, 24 authors | 69%11 favorable, 5 not, 16 authors | 63%22 favorable, 13 not, 35 authors | 56%27 favorable, 21 not, 45 authors | 80%24 favorable, 6 not, 28 authors | 56%20 favorable, 16 not, 36 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 61%25 favorable, 16 not, 40 authors | Only concerns on record0 favorable, 4 not, 4 authors | 59%20 favorable, 14 not, 32 authors | Only praise on record3 favorable, 0 not, 3 authors | 50%3 favorable, 3 not, 6 authors | 58%11 favorable, 8 not, 18 authors | 36%5 favorable, 9 not, 14 authors | 43%16 favorable, 21 not, 36 authors | 86%6 favorable, 1 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 62%13 favorable, 8 not, 21 authors | 86%18 favorable, 3 not, 21 authors | 67%14 favorable, 7 not, 21 authors | 76%47 favorable, 15 not, 61 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record2 favorable, 0 not, 2 authors | 53%8 favorable, 7 not, 15 authors | 44%8 favorable, 10 not, 17 authors | 71%24 favorable, 10 not, 34 authors | 57%4 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors |
| Tool use and structured output | 40%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 | 56%5 favorable, 4 not, 9 authors | No accounts yet | 67%6 favorable, 3 not, 9 authors | 40%4 favorable, 6 not, 10 authors | 46%6 favorable, 7 not, 13 authors | 30%3 favorable, 7 not, 10 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 70%7 favorable, 3 not, 10 authors | 57%4 favorable, 3 not, 7 authors | 50%4 favorable, 4 not, 8 authors | 50%4 favorable, 4 not, 8 authors | 29%2 favorable, 5 not, 7 authors | 33%4 favorable, 8 not, 12 authors | 70%7 favorable, 3 not, 10 authors | 43%3 favorable, 4 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 25%2 favorable, 6 not, 8 authors | 47%7 favorable, 8 not, 15 authors | 67%4 favorable, 2 not, 6 authors | 54%7 favorable, 6 not, 12 authors | Only concerns on record0 favorable, 1 not, 1 author | 59%10 favorable, 7 not, 17 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 38%5 favorable, 8 not, 13 authors | Only concerns on record0 favorable, 5 not, 5 authors | 38%6 favorable, 10 not, 16 authors | Only praise on record2 favorable, 0 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | 67%4 favorable, 2 not, 6 authors | 80%8 favorable, 2 not, 10 authors | 33%2 favorable, 4 not, 6 authors | 57%4 favorable, 3 not, 7 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only concerns on record0 favorable, 4 not, 4 authors | 46%6 favorable, 7 not, 13 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 5 not, 5 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author |
| Long context | 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 | Only concerns on record0 favorable, 3 not, 3 authors | No accounts yet | 29%2 favorable, 5 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 80%8 favorable, 2 not, 10 authors | 63%5 favorable, 3 not, 8 authors | 67%4 favorable, 2 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 33%2 favorable, 4 not, 6 authors | 60%6 favorable, 4 not, 10 authors | 50%4 favorable, 4 not, 7 authors | 71%5 favorable, 2 not, 7 authors | 64%7 favorable, 4 not, 11 authors | 40%4 favorable, 6 not, 10 authors | 40%2 favorable, 3 not, 5 authors | 50%4 favorable, 4 not, 8 authors | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 20%1 favorable, 4 not, 5 authors | 44%7 favorable, 9 not, 16 authors | Only praise on record1 favorable, 0 not, 1 author | 58%7 favorable, 5 not, 12 authors | No accounts yet | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | No accounts yet | 42%5 favorable, 7 not, 12 authors | No accounts yet | No accounts yet | 40%2 favorable, 3 not, 5 authors | 60%3 favorable, 2 not, 5 authors | No accounts yet | 40%2 favorable, 3 not, 5 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 3 not, 3 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 75%6 favorable, 2 not, 8 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | No accounts yet |
| Developer experience | 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 | 25%3 favorable, 9 not, 12 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 38%6 favorable, 10 not, 16 authors | 50%7 favorable, 7 not, 14 authors | 25%3 favorable, 9 not, 12 authors | 29%2 favorable, 5 not, 7 authors | 25%3 favorable, 9 not, 12 authors | 53%10 favorable, 9 not, 19 authors | 29%4 favorable, 10 not, 14 authors | 57%4 favorable, 3 not, 7 authors | 45%5 favorable, 6 not, 11 authors | 67%8 favorable, 4 not, 12 authors | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | 50%3 favorable, 3 not, 6 authors | 33%3 favorable, 6 not, 9 authors | 39%7 favorable, 11 not, 17 authors | Only concerns on record0 favorable, 7 not, 7 authors | 40%8 favorable, 12 not, 20 authors | No accounts yet | 35%8 favorable, 15 not, 23 authors | No accounts yet | 9%1 favorable, 10 not, 11 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | 13%2 favorable, 14 not, 16 authors | Only concerns on record0 favorable, 9 not, 9 authors | 25%5 favorable, 15 not, 20 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 7 not, 7 authors | 11%1 favorable, 8 not, 9 authors | Only concerns on record0 favorable, 3 not, 3 authors | 33%5 favorable, 10 not, 15 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 6 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet |
| Cost | 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 | 55%12 favorable, 10 not, 21 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 69%20 favorable, 9 not, 29 authors | 45%10 favorable, 12 not, 22 authors | 56%15 favorable, 12 not, 27 authors | 20%4 favorable, 16 not, 20 authors | 43%3 favorable, 4 not, 7 authors | 39%7 favorable, 11 not, 17 authors | 8%1 favorable, 11 not, 12 authors | 40%6 favorable, 9 not, 14 authors | 50%7 favorable, 7 not, 13 authors | 50%6 favorable, 6 not, 12 authors | 33%7 favorable, 14 not, 20 authors | 53%8 favorable, 7 not, 15 authors | 29%4 favorable, 10 not, 12 authors | 38%3 favorable, 5 not, 8 authors | 35%7 favorable, 13 not, 20 authors | 58%14 favorable, 10 not, 23 authors | Only praise on record7 favorable, 0 not, 7 authors | 50%8 favorable, 8 not, 16 authors | Only concerns on record0 favorable, 1 not, 1 author | 66%25 favorable, 13 not, 37 authors | Only praise on record2 favorable, 0 not, 2 authors | 40%10 favorable, 15 not, 25 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 8 not, 8 authors | 19%5 favorable, 21 not, 26 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record4 favorable, 0 not, 4 authors | 80%12 favorable, 3 not, 15 authors | 50%6 favorable, 6 not, 12 authors | 76%16 favorable, 5 not, 21 authors | 35%8 favorable, 15 not, 23 authors | 71%5 favorable, 2 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | Only concerns on record0 favorable, 2 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only praise on record3 favorable, 0 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author |
| Speed | 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 | 57%4 favorable, 3 not, 7 authors | Only praise on record1 favorable, 0 not, 1 author | 74%14 favorable, 5 not, 19 authors | 88%14 favorable, 2 not, 16 authors | 46%6 favorable, 7 not, 13 authors | 44%4 favorable, 5 not, 9 authors | 60%3 favorable, 2 not, 5 authors | 44%4 favorable, 5 not, 9 authors | 57%4 favorable, 3 not, 7 authors | 31%4 favorable, 9 not, 13 authors | 63%5 favorable, 3 not, 8 authors | 17%1 favorable, 5 not, 6 authors | 36%4 favorable, 7 not, 11 authors | 73%8 favorable, 3 not, 11 authors | 78%7 favorable, 2 not, 9 authors | 75%6 favorable, 2 not, 8 authors | 45%5 favorable, 6 not, 11 authors | 61%19 favorable, 12 not, 31 authors | 53%10 favorable, 9 not, 17 authors | 35%6 favorable, 11 not, 16 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 68%21 favorable, 10 not, 30 authors | Only concerns on record0 favorable, 1 not, 1 author | 21%4 favorable, 15 not, 19 authors | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | 21%3 favorable, 11 not, 14 authors | Only concerns on record0 favorable, 2 not, 2 authors | 29%5 favorable, 12 not, 17 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only praise on record2 favorable, 0 not, 2 authors | 44%4 favorable, 5 not, 9 authors | 65%13 favorable, 7 not, 20 authors | 33%3 favorable, 6 not, 9 authors | 20%3 favorable, 12 not, 15 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | No accounts yet | 33%7 favorable, 14 not, 21 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author |
| Reliability | 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 | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 3 not, 3 authors | 20%1 favorable, 4 not, 5 authors | 18%2 favorable, 9 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 9%1 favorable, 10 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 63%5 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 17%2 favorable, 10 not, 12 authors | 18%2 favorable, 9 not, 11 authors | 17%1 favorable, 5 not, 6 authors | 20%3 favorable, 12 not, 15 authors | 38%6 favorable, 10 not, 16 authors | 29%2 favorable, 5 not, 7 authors | 40%4 favorable, 6 not, 10 authors | 5%1 favorable, 18 not, 19 authors | 15%3 favorable, 17 not, 20 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%3 favorable, 19 not, 22 authors | Only concerns on record0 favorable, 1 not, 1 author | 42%5 favorable, 7 not, 12 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 8%1 favorable, 12 not, 13 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 38%3 favorable, 5 not, 8 authors | Only concerns on record0 favorable, 4 not, 4 authors | 22%2 favorable, 7 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 60%3 favorable, 2 not, 5 authors | 33%2 favorable, 4 not, 5 authors | Only concerns on record0 favorable, 7 not, 7 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author |
The 21 accounts behind GPT-6.1 Terra's figures
GILD searched Hacker News, GitHub and X for accounts that name GPT-6.1 Terra.
Quality and reasoning 33%
- Favorable
GPT-6.1 Terra passed 40 of 43 questions (93%) for $1.31 for the whole exam, half the cost of GPT-6.1 Sol, which scored 43.
GPT-6.1 Terra Benchmark Results for Data Analysis. Plotly, maker of the Plotly Studio analytics agent and the Dash framework, self-described, Oct 26, 2026. GPT-6.1 Terra through OpenRouter at its default reasoning setting on Plotly's private 43-question data analytics exam.
- Favorable
GPT-6.1 Terra scored 84, one point over Grok 4.7 (83)
GPT-6.1 Terra. thefourthchime, Hacker News commenter, self-described, Oct 27, 2026. GPT-6.1 Terra on PacBench, a Pac-Man build bake-off, against Grok 4.7.
- Favorable
Same car. Better result from Terra.
X post by @AlphaDevj. Alpha (AlphaDevj), developer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra against GPT-6.1 Sol, both at Extra High, on the same car computer use task.
- Unfavorable
But Haiku produced the more realistic result — better lighting, fog and fire.
X post by @AlphaDevj. Alpha (AlphaDevj), developer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra against Claude Haiku 5.5 on the same build.
- Unfavorable
less keen on refactoring when the grid scales to 22×22.
X post by @RichDevLab. Richard Thomas (RichDevLab), architect and author of farmerbench.dev per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in Codex at medium effort on three 6-hour FarmerBench seeds.
- Unfavorable
blind test vs the model we already run: - lost 14 to 3
X post by @RimasXYZ. Rimas (RimasXYZ), building adrio.ai per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in a blind test on the author's ad prompt agent against the model already in production.
- Unfavorable
Tried 6.1 Terra in codex, not very impressed with it, I 'll stick to Sol.
X post by @Bi11Leou. Bill Leoutsakos (Bi11Leou), computer engineering at Cambridge per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra in Codex.
- Unfavorable
It still bypass the "do not delete anything without my tell you so" rule.
X post by @xVelns. xVelns, X user, self-described, Oct 27, 2026. GPT-6.1 Terra at Max effort with a do-not-delete rule.
- Unfavorable
even this watered down version from @opencode is faster, cheaper and more capable than @OpenAI GPT 6.1-Terra High
X post by @GCC_Trader. Camel Trader (GCC_Trader), X user, self-described, Oct 27, 2026. GPT-6.1 Terra (GPT 6.1-Terra) at High effort against DeepSeek in OpenCode.
Tool use and structured output 40%
- Favorable
The new Terra 6.1 is pretty good at doing user testing as well via computer use, going through all the features and noting any bugs or inconsistencies.
Genie 4. pigpop, Hacker News commenter, self-described, Oct 28, 2026. GPT-6.1 Terra (Terra 6.1) user testing a game project through computer use.
- Unfavorable
I ask it to implement something, but it doesn't follow through. It keeps stopping without taking the next concrete step.
gpt 6.1 terra bad. hybridapp323, GitHub issue author, self-described, Oct 28, 2026. GPT-6.1 Terra (gpt 6.1 terra) in Codex CLI v0.165 implementing features.
- Unfavorable
I asked GPT 6.1 Terra to perform a test run on a personal Computer Use benchmark, but it stopped very early because it was "too complex". This has happened 3 times now.
X post by @ishuagra02. Ishu Agrawal (ishuagra02), AI news and demos poster per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra on the author's personal computer use benchmark.
- Favorable
when a locked hat crashed its script on seed 3, it read the docs, wrote a one-line fix and recovered in a minute.
X post by @RichDevLab. Richard Thomas (RichDevLab), architect and author of farmerbench.dev per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in Codex at medium effort on three 6-hour FarmerBench seeds.
- Unfavorable
Stops tasks randomly. Was instructed to launch subagents but claimed GPT Terra 6.1 isn't an available model so it stopped and gave up.
X post by @synthshareai. Petra (synthshareai), GenAI explorer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra (GPT Terra 6.1) in Codex launching subagents.
Long context Only concerns on record
- Unfavorable
GPT Terra 6.1 worked great for a hour or two for me. Then it turned to slop.
X post by @GDWizard00. GDWizard (GDWizard00), AI, Web3 and gaming builder per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra (GPT Terra 6.1) over a session of one repeated task.
Developer experience Only concerns on record
- Unfavorable
This appears to be a stale or incorrect model label in the VS Code extension during the rollout
VS Code Codex showed GPT-6 Terra while session metadata used gpt-6.1-terra during Oct 26 rollout. pearson-bailey, GitHub issue author, self-described, Oct 26, 2026. GPT-6.1 Terra (gpt-6.1-terra) in the Codex VS Code extension at xhigh effort during the October 26 rollout.
- Unfavorable
Hermes saves `agent.reasoning_effort: max` and builds `reasoning.effort: xhigh` for it.
[Bug]: GPT-6.1 Terra max reasoning is silently clamped to xhigh on Codex Responses. Tavitsri, GitHub issue author, self-described, Oct 27, 2026. GPT-6.1 Terra (gpt-6.1-terra) through Hermes Agent's Codex Responses route.
Cost 80%
- Favorable
It also joins the cost-accuracy frontier: no model we've tested is both cheaper and more accurate.
GPT-6.1 Terra Benchmark Results for Data Analysis. Plotly, maker of the Plotly Studio analytics agent and the Dash framework, self-described, Oct 26, 2026. GPT-6.1 Terra through OpenRouter at its default reasoning setting on Plotly's private 43-question data analytics exam.
- Favorable
The cheap models keep getting better.
GPT-6.1 Terra. thefourthchime, Hacker News commenter, self-described, Oct 27, 2026. GPT-6.1 Terra on PacBench, a Pac-Man build bake-off, against Grok 4.7.
- Favorable
GPT-6.1 Terra is an AWESOME release for anyone using the API in agentic production applications where cost matters.
GPT-6.1 Terra. __jl__, Hacker News commenter, self-described, Oct 26, 2026. GPT-6.1 Terra under internal evals for an agentic production application on the OpenAI API.
- Favorable
Terra also raised 27 valid majors against 9, and 4 invalid findings against 0, at 55% of Sol's Codex token count.
Holdout for gpt-6.1-terra against gpt-6.1-sol in revmux, pre-registered. Seigiard, GitHub issue author, self-described, Oct 28, 2026. GPT-6.1 Terra (gpt-6.1-terra) as the Codex reviewer in a 27-round revmux code-review pilot against gpt-6.1-sol.
- Favorable
Terra: 6m 22s — $0.29 Sol: 16m 01s — $0.80
X post by @AlphaDevj. Alpha (AlphaDevj), developer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra against GPT-6.1 Sol, both at Extra High, on the same car computer use task.
- Favorable
Terra: $0.93 — ~21 min Haiku: $2.50 — ~56 min
X post by @AlphaDevj. Alpha (AlphaDevj), developer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra against Claude Haiku 5.5 on the same build.
- Favorable
it averaged 62.16 (58.47 / 66.34 / 61.68) at $0.22 and 2m 56s a run
X post by @RichDevLab. Richard Thomas (RichDevLab), architect and author of farmerbench.dev per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in Codex at medium effort on three 6-hour FarmerBench seeds.
- Unfavorable
2x slower - 16x the cost
X post by @RimasXYZ. Rimas (RimasXYZ), building adrio.ai per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in a blind test on the author's ad prompt agent against the model already in production.
- Favorable
6.1-terra is a very interesting model in terms of value for money
X post by @Parad0x80. Parad0x80, CTO per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra in the API and in Codex as a sub-agent.
- Unfavorable
I ate through 30% usage yesterday on Terra on my $200/mo plan.
X post by @Maticated. Mat Windle (Maticated), AI developer for work per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra in Codex on the $200 a month plan.
Speed 83%
- Favorable
A typical question took 15 seconds , which makes it the fastest model on our leaderboard of 35 to score 40 or more.
GPT-6.1 Terra Benchmark Results for Data Analysis. Plotly, maker of the Plotly Studio analytics agent and the Dash framework, self-described, Oct 26, 2026. GPT-6.1 Terra through OpenRouter at its default reasoning setting on Plotly's private 43-question data analytics exam.
- Favorable
in 5.4 min for $0.19 vs Grok's 36.5 min
GPT-6.1 Terra. thefourthchime, Hacker News commenter, self-described, Oct 27, 2026. GPT-6.1 Terra on PacBench, a Pac-Man build bake-off, against Grok 4.7.
- Favorable
seems 6.1 terra is indeed fast while I switch from the 6.1 sol when do automated test.
GPT-6.1 Terra. mintflow, Hacker News commenter, self-described, Oct 27, 2026. GPT-6.1 Terra in automated tests after switching from GPT-6.1 Sol.
- Favorable
Less than half the time.
X post by @AlphaDevj. Alpha (AlphaDevj), developer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra against GPT-6.1 Sol, both at Extra High, on the same car computer use task.
- Favorable
Terra was much faster and cheaper.
X post by @AlphaDevj. Alpha (AlphaDevj), developer per the X bio, self-described, Oct 27, 2026. GPT-6.1 Terra against Claude Haiku 5.5 on the same build.
- Unfavorable
7/24 runs timed out - 2x slower
X post by @RimasXYZ. Rimas (RimasXYZ), building adrio.ai per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in a blind test on the author's ad prompt agent against the model already in production.
Reliability Only concerns on record
- Unfavorable
- 7/24 runs timed out
X post by @RimasXYZ. Rimas (RimasXYZ), building adrio.ai per the X bio, self-described, Oct 26, 2026. GPT-6.1 Terra in a blind test on the author's ad prompt agent against the model already in production.