RankingEffort benchmarks
GPT-6 Sol
147 measured results · 7 effort settings · 64 benchmark/harness combinations
Change model
Capability profile
One configuration, seven capabilities
- AGPT-6 Sol · Max4 of 7 capabilities supported
Gaps are unknown, not zero. Hollow points are preliminary.
Agentic
A55.1SupportedHard reasoning
A68.4SupportedCoding
A74.5SupportedHuman pref
UnknownKnowledge
A63.7SupportedMultimodal
A56.0PreliminaryLong context
A79.6Preliminary
Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.
Capability score evidence
GPT-6 Sol · Max: 66.4 overall comparison score. Meets the overall evidence requirements.
Shared-result disagreement. This aggregate order conflicts with matched benchmark results against 2 other configurations. Different test coverage and opponents affect the fit. Inspect published results before treating the rank as conclusive.
Which sources carry the weight?
- OpenAI · 23.6% direct comparison weight · provider report
- Epoch AI · 11.9% direct comparison weight · independent of the model provider
- Cognition · 11.7% direct comparison weight · independent of the model provider
- LiveBench · 11.7% direct comparison weight · independent of the model provider
- Vals AI · 11.4% direct comparison weight · independent of the model provider
- ARC Prize · 11.3% direct comparison weight · independent of the model provider
- Artificial Analysis · 10.0% direct comparison weight · independent of the model provider
- Terminal-Bench · 8.4% direct comparison weight · independent of the model provider
Which benchmark families carry the weight?
- FrontierCode · 11.7% direct comparison weight
- Terminal-Bench · 10.5% direct comparison weight
- ARC-AGI · 5.9% direct comparison weight
- AutomationBench · 5.5% direct comparison weight
- GDP.pdf · 5.5% direct comparison weight
- Other families (30) · 60.9% direct comparison weight
These shares describe direct comparison weight, not fractions of the final score or confidence. Source balancing does not give every family equal weight or remove correlations between overlapping sources.
How sensitive is this score?
The audit removes one source at a time and refits against the same overall reference panel. These published results use the matching dataset audited 2026-10-31.
Both ranks use the same surviving configurations for each removal. The cohort starts with 446 configurations supported in the original audit, including separate effort settings. These are diagnostic positions, not the default leaderboard ranks. Eligibility is not rechecked after removal.
| Removed source | Rank before → after | Rank movement | Cohort remaining / lost support | Score after (change) |
|---|---|---|---|---|
| Artificial Analysis | 43 → 43 | No movement | 203 remaining / 243 lost | 67.3 |
| ARC Prize | 43 → 47 | Down 4 | 446 remaining / 0 lost | 68.5 |
| Datacurve | 43 → 42 | Up 1 | 446 remaining / 0 lost | 62.1 |
| LiveCodeBench | 43 → 43 | No movement | 446 remaining / 0 lost | 66.4 |
| Scale | 43 → 43 | No movement | 446 remaining / 0 lost | 67.4 |
| Terminal-Bench | 43 → 46 | Down 3 | 446 remaining / 0 lost | 64.3 |
| Cognition | 43 → 42 | Up 1 | 446 remaining / 0 lost | 62.1 |
| LiveBench | 43 → 38 | Up 5 | 445 remaining / 1 lost | 70.5 |
| SWE-rebench | 43 → 43 | No movement | 446 remaining / 0 lost | 65.9 |
| Epoch AI | 43 → 45 | Down 2 | 433 remaining / 13 lost | 65.8 |
| Vals AI | 43 → 38 | Up 5 | 445 remaining / 1 lost | 70.7 |
| Provider reports · Anthropic | 43 → 43 | No movement | 446 remaining / 0 lost | 66.3 |
| Provider reports · Moonshot AI | 43 → 43 | No movement | 446 remaining / 0 lost | 66.1 |
| Provider reports · Meta | 43 → 42 | Up 1 | 446 remaining / 0 lost | 66.3 |
| Provider reports · Mistral | 43 → 43 | No movement | 446 remaining / 0 lost | 66.4 |
| Provider reports · OpenAI | 43 → 36 | Up 7 | 446 remaining / 0 lost | 72.6 |
| All provider reports | 43 → 35 | Up 8 | 446 remaining / 0 lost | 72.1 |
Lost support means a configuration no longer has a comparison path to the complete reference panel. Its rank is unavailable. A surviving path alone does not establish leaderboard eligibility.
Overlapping sources may remain correlated even with source balancing. Leave-one-source-out movement is a sensitivity diagnostic, not a spread of source-specific ranks or a confidence measure. Scoring methodology · Dated configuration audit
Every benchmark family
| Removed evidence | Recomputed score | Change |
|---|---|---|
| frontiercode | 62.1 | -4.3 |
| deepswe | 62.1 | -4.3 |
| terminal-bench | 63.5 | -3.0 |
| arc-agi | 68.4 | +2.0 |
| vals-finance-agent | 67.7 | +1.3 |
| vals-legal-research | 67.6 | +1.2 |
| vibe-code | 65.3 | -1.1 |
| vals-tax-agent | 67.6 | +1.1 |
| vals-code-migration | 65.4 | -1.1 |
| simpleqa | 67.5 | +1.0 |
| livebench-instructions | 67.2 | +0.8 |
| vals-excel-modeling | 65.6 | -0.8 |
| mmmu-pro | 67.2 | +0.7 |
| frontiermath | 65.7 | -0.7 |
| hle | 67.0 | +0.6 |
| arc-agi-3 | 67.0 | +0.6 |
| swe-rebench | 65.9 | -0.5 |
| livebench-data | 65.9 | -0.5 |
| livebench-coding | 66.0 | -0.4 |
| epoch-game-puzzles | 66.1 | -0.3 |
| multi-swe-bench | 66.7 | +0.3 |
| swe-atlas-qna | 66.2 | -0.3 |
| mmlu-pro | 66.7 | +0.2 |
| ifbench | 66.2 | -0.2 |
| swe-atlas-test-writing | 66.3 | -0.2 |
| automationbench | 66.3 | -0.2 |
| tau-bench | 66.3 | -0.2 |
| omniscience | 66.6 | +0.2 |
| aime | 66.3 | -0.1 |
| terminal-bench-science | 66.3 | -0.1 |
| livebench-math | 66.3 | -0.1 |
| gdpval | 66.5 | +0.1 |
| livebench-language | 66.3 | -0.1 |
| critpt | 66.5 | +0.1 |
| itbench | 66.4 | -0.1 |
| gdp-pdf | 66.5 | +0.1 |
| aa-lcr | 66.5 | +0.1 |
| gpqa | 66.4 | -0.1 |
| analyst-agent | 66.5 | +0.1 |
| enterprise-ops | 66.5 | +0.1 |
| apex-agents | 66.5 | +0.0 |
| swe-atlas-refactoring | 66.4 | -0.0 |
| enigma-eval | 66.4 | -0.0 |
| briefcase | 66.4 | -0.0 |
| harvey | 66.4 | +0.0 |
| livebench-reasoning | 66.4 | +0.0 |
| livecodebench | 66.4 | -0.0 |
| math500 | 66.4 | -0.0 |
| swe-bench-pro | 66.4 | +0.0 |
| gmmlu | 66.4 | -0.0 |
What evidence is missing from the fit?
Across all collected settings for this model: 221 observations, 158 contributing, 0 matched without graph weight and 63 excluded. Counts do not establish rank eligibility.
- 6 · Original SciCode grading defects are under review; retained as supporting evidence, excluded from aggregate and capability scores. Corrected SciCode-Verified requires a separate protocol review. Sources: https://arxiv.org/abs/2608.04975 and https://artificialanalysis.ai/evaluations/scicode
- 4 · Benchmark family or source protocol has not been reviewed
- 4 · Evaluator has not been reviewed for independent admission
- 25 · Provider-published lab self-report. Shown as a labeled claim and not admitted as a matched board comparison.
- 5 · Private user-flagged prompt protocol needs separate review before capability scoring; retained as an exact lower-is-better sourced claim.
- 4 · Safety failure behavior is not a capability or intelligence score.
- 13 · Supporting evidence outside the reviewed capability core
- 2 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
Benchmark results
Reviewed retained observations are in use. October 2026 Real-SWE board has no 95% confidence whisker, so these scores stay at the 2026-10-18 retrieval. Original source retrieval 2026-10-18; source updated 2026-10-18.
| Benchmark / source | Low | Medium | High | XHigh | Max | None | Non-reasoning |
|---|---|---|---|---|---|---|---|
AA-Briefcase EloBenchmark detailsAA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-31. | 885.28 Elo Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 1,147.76 Elo Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 1,266.21 Elo Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 1,358.03 Elo Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 1,475.81 Elo Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 1,104.61 Elo Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
AA-LCR v1.1Benchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 79.33% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 82.33% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 83.67% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 81.33% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 83.67% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 64% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
AutomationBench-AABenchmark detailsShare of task objectives completed with no guardrail violations · Higher is better · Benchmark developed by Zapier · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 53.89% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 57.97% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 60.13% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 61.69% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 61.63% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 34.18% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
CritPtBenchmark detailsBenchmark developed by Argonne and UIUC, with contributions from 60+ researchers globally · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 16.29% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 24.57% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 25.43% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 28% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 30.86% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 4% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
GDP.pdf: All-pass RateBenchmark detailsShare of attempts where every atomic criterion passed · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 24.2% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 23.8% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 24.4% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 24.6% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 25.2% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 17% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
GDPval-AA v2.1 LeaderboardBenchmark detailsElo rating for performance on real-world work tasks · Anchored to DeepSeek V4.1 Flash (max) at 1600 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-31. | 1,201.12 Elo Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 1,351.87 Elo Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 1,403.81 Elo Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 1,466.31 Elo Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 1,515.88 Elo Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 1,254.28 Elo Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
Harvey LAB-AA v1.1: Hallucination-Gated All-Pass RateBenchmark detailsAverage over tasks of the share of the judge panel finding every rubric criterion passed, with a task zeroed on any material hallucination · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 3.61% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | Not reported |
Humanity's Last ExamBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 34.94% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 40.96% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 44.11% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 46.29% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 47.91% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 18.4% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
ITBench-AABenchmark detailsCombined public and private Site Reliability Engineering (SRE) tasks · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 49.44% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | Not reported |
MLCR-AABenchmark detailsShare of responses judged complete with no claim contradicting the record · Expert + compound (hard) sets · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 25.56% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 28.89% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 29.44% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 32.22% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 33.89% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 22.78% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
MMMU-ProBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 80.17% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 80.4% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 81.97% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 82.54% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 82.95% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 70.35% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
SciCodeBenchmark detailsBenchmark curated by scientists across 16 disciplines. SciCode is under review following an independent audit of the dataset · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 50.23% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 53.82% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 54.86% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 55.09% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 57.64% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 47.34% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
Terminal-Bench-Science 0.1Benchmark detailsShare of tasks passed (pass@1), averaged over three repeats · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 3.33% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 8.57% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 17.14% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 17.62% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 30% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 5.71% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
Terminal-Bench v4.0Benchmark detailsBenchmark developed by the Laude Institute, Stanford, and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-31. | 9.09% Reported settingsGPT-6 Sol (Low); Model source: https://artificialanalysis.ai/models/gpt-6-sol-low | 18.69% Reported settingsGPT-6 Sol (Medium); Model source: https://artificialanalysis.ai/models/gpt-6-sol-medium | 26.26% Reported settingsGPT-6 Sol (High); Model source: https://artificialanalysis.ai/models/gpt-6-sol-high | 30.3% Reported settingsGPT-6 Sol (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-6-sol-xhigh | 43.94% Reported settingsGPT-6 Sol (Max); Model source: https://artificialanalysis.ai/models/gpt-6-sol | Not reported | 13.13% Reported settingsGPT-6 Sol (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-6-sol-non-reasoning |
ARC-AGI-2Benchmark detailsOriginal public board. Configuration and task coverage may differ; inspect source. Unit: percent. Source collected 2026-10-31. | 31.53% Reported settingsGPT-6 Sol (Low); Source model ID: openai-gpt-6-sol-low; 120 tasks | 57.78% Reported settingsGPT-6 Sol (Medium); Source model ID: openai-gpt-6-sol-medium; 120 tasks | 68.89% Reported settingsGPT-6 Sol (High); Source model ID: openai-gpt-6-sol-high; 120 tasks | 78.06% Reported settingsGPT-6 Sol (XHigh); Source model ID: openai-gpt-6-sol-xhigh; 120 tasks | 89.58% Reported settingsGPT-6 Sol (Max); Source model ID: openai-gpt-6-sol-max; 120 tasks | 1.67% Reported settingsGPT-6 Sol (None); Source model ID: openai-gpt-6-sol-none; 120 tasks | Not reported |
ARC-AGI-3 · provider-adapterBenchmark detailsARC-AGI-3; Provider Adapter. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-31. | 1.76% Reported settingsARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group openai-gpt-6-sol; variant provider-adapter-low; public-demo task scores are excluded | 4.93% Reported settingsARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group openai-gpt-6-sol; variant provider-adapter-medium; public-demo task scores are excluded | 5.86% Reported settingsARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group openai-gpt-6-sol; variant provider-adapter-high; public-demo task scores are excluded | 9.45% Reported settingsARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group openai-gpt-6-sol; variant provider-adapter-xhigh; public-demo task scores are excluded | 23.03% Reported settingsARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group openai-gpt-6-sol; variant provider-adapter-max; public-demo task scores are excluded | 1.21% Reported settingsARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group openai-gpt-6-sol; variant provider-adapter-none; public-demo task scores are excluded | Not reported |
ARC-AGI-3 · standardBenchmark detailsARC-AGI-3; Standard. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-31. | 0.13% Reported settingsARC-AGI-3 Semi-Private verified summary; Standard harness; source group openai-gpt-6-sol; variant low; public-demo task scores are excluded | 0.42% Reported settingsARC-AGI-3 Semi-Private verified summary; Standard harness; source group openai-gpt-6-sol; variant medium; public-demo task scores are excluded | 0.9% Reported settingsARC-AGI-3 Semi-Private verified summary; Standard harness; source group openai-gpt-6-sol; variant high; public-demo task scores are excluded | 1.8% Reported settingsARC-AGI-3 Semi-Private verified summary; Standard harness; source group openai-gpt-6-sol; variant xhigh; public-demo task scores are excluded | 4.62% Reported settingsARC-AGI-3 Semi-Private verified summary; Standard harness; source group openai-gpt-6-sol; variant max; public-demo task scores are excluded | 0.28% Reported settingsARC-AGI-3 Semi-Private verified summary; Standard harness; source group openai-gpt-6-sol; variant none; public-demo task scores are excluded | Not reported |
FrontierCode 1.1 · extended-codexBenchmark detailsFrontierCode 1.1; codex. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-31. | 50.55% Reported settingsFrontierCode 1.1; extended; 150 tasks; codex; source effort low; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.0013 | 57.11% Reported settingsFrontierCode 1.1; extended; 150 tasks; codex; source effort medium; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.0013 | 59.62% Reported settingsFrontierCode 1.1; extended; 150 tasks; codex; source effort high; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0 | 59.13% Reported settingsFrontierCode 1.1; extended; 150 tasks; codex; source effort xhigh; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.0013 | 60.69% Reported settingsFrontierCode 1.1; extended; 150 tasks; codex; source effort max; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0 | Not reported | Not reported |
FrontierCode 1.1 · main-codexBenchmark detailsFrontierCode 1.1; codex. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-31. | 37.28% Reported settingsFrontierCode 1.1; main; 100 tasks; codex; source effort low; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.002 | 45.92% Reported settingsFrontierCode 1.1; main; 100 tasks; codex; source effort medium; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0 | 47.7% Reported settingsFrontierCode 1.1; main; 100 tasks; codex; source effort high; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0 | 48.45% Reported settingsFrontierCode 1.1; main; 100 tasks; codex; source effort xhigh; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.002 | 49.27% Reported settingsFrontierCode 1.1; main; 100 tasks; codex; source effort max; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0 | Not reported | Not reported |
Terminal-Bench 4.0 · codexBenchmark detailsTerminal-Bench 4.0; Codex. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 49.4% Reported settingsTerminal-Bench 4.0.0; 66 tasks; Codex; effort max; reported margin ±3.2 percentage points, confidence level unspecified; release date 2026-09-22; board checked 2026-10-23 | Not reported | Not reported |
LiveBench · AMPS Hard · 2026-06-25Benchmark detailsLiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 98% Reported settingsLiveBench official task evaluation; livebench-2026-06-25-AMPS_Hard; gpt-6-sol-max; checkpoint=gpt-6-sol | Not reported | Not reported |
LiveBench · code completion · 2026-06-25Benchmark detailsLiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 80.44% Reported settingsLiveBench official task evaluation; livebench-2026-06-25-code_completion; gpt-6-sol-max; checkpoint=gpt-6-sol | Not reported | Not reported |
LiveBench · code generation · 2026-06-25Benchmark detailsLiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 83.1% Reported settingsLiveBench official task evaluation; livebench-2026-06-25-code_generation; gpt-6-sol-max; checkpoint=gpt-6-sol | Not reported | Not reported |
LiveBench · connections · 2026-06-25Benchmark detailsLiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 100% Reported settingsLiveBench official task evaluation; livebench-2026-06-25-connections; gpt-6-sol-max; checkpoint=gpt-6-sol | Not reported | Not reported |
LiveBench · consecutive events · 2026-06-25Benchmark detailsLiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-31. | Not reported | Not reported | Not reported | Not reported | 89.55% Reported settingsLiveBench official task evaluation; livebench-2026-06-25-consecutive_events; gpt-6-sol-max; checkpoint=gpt-6-sol | Not reported | Not reported |
What these comparisons mean
Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.
These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.
Download all effort benchmark results · 8,399 results across 259 models · Collected 2026-10-31