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OpenAI
Track OpenAI model scores across public AI benchmarks including GPQA Diamond, ECI, GDPval-AA, FrontierMath, and AIME (OTIS Mock). Each result is shown one benchmark at a time, with source links and evaluation dates — no blended score or composite ranking. 21 models tracked, spanning GPT, o-series, OpenAI o-series (o3), and GPT OSS.
Models 21
GPT-5.6 Luna
GPT · gpt-5.6 luna
2026-07-09
7 results
GPT-5.6 Terra
GPT · gpt-5.6 terra
2026-07-09
7 results
GPT-5.6 Sol Ultra
GPT · gpt-5.6 sol ultra
2026-07-09
2 results
GPT-5.6 Sol
GPT · gpt-5.6 sol
2026-07-09
7 results
GPT-5.5 Pro
GPT · gpt-5.5 pro
2026-04-23
8 results
GPT-5.5
GPT · gpt-5.5
2026-04-23
41 results
GPT-5.4-mini
GPT · gpt-5.4-mini
2026-03-17
1 results
GPT-5.4 Pro
GPT · gpt-5.4 pro
2026-03-05
13 results
GPT-5.4
GPT · gpt-5.4
2026-03-05
46 results
GPT-5.3-Codex
GPT · gpt-5.3-codex
2026-02-05
14 results
GPT-5.2-Codex
GPT · gpt-5.2-codex
2025-12-18
8 results
GPT-5.2
GPT · gpt-5.2
2025-12-11
47 results
GPT-5.1
GPT · gpt-5.1
2025-11-12
37 results
GPT-5 mini
GPT · gpt-5-mini
2025-08-07
29 results
GPT-5
GPT · gpt-5
2025-08-07
49 results
GPT-OSS-120B
GPT OSS · gpt-oss-120b
2025-08-05
25 results
OpenAI o3-pro
OpenAI o-series (o3) · o3 pro
2025-06-10
8 results
o4-mini
o-series · o4-mini
2025-04-16
38 results
o3
o-series · o3
2025-04-16
44 results
GPT-4.1
GPT · gpt-4.1
2025-04-14
34 results
GPT-4o
GPT · gpt-4o
2024-05-13
43 results
Progress by benchmark
Show progress on
Single benchmark only
This view shows GPQA Diamond (accuracy) only. Other benchmarks use different metrics and are not directly comparable.
Progress matrix
| Model | SWE-bench Verified % resolved | Terminal-Bench 2.1 task success | DeepSWE % resolved | GPQA Diamond accuracy | LiveCodeBench Pro Codeforces Elo | Humanity's Last Exam accuracy | LiveBench score | SWE-bench Pro % resolved | Berkeley Function Calling Leaderboard accuracy | MMMU-Pro accuracy | LMArena source-defined rating | ARC-AGI-1 accuracy | ARC-AGI-2 accuracy | ARC-AGI-3 accuracy | FrontierMath accuracy | AIME (OTIS Mock) accuracy | SimpleQA Verified accuracy | GBA Eval overall score | WeirdML average accuracy | MCP Atlas pass rate | Remote Labor Index automation rate | Artificial Analysis Intelligence Index Index | Epoch Capabilities Index Index | Aider Polyglot % correct | SWE-rebench Resolved rate (pass@1) | MMLU-Pro accuracy | OSWorld task success rate | GAIA: A Benchmark for General AI Assistants accuracy | BrowseComp accuracy | τ²-bench (Telecom) pass^1 | AIME 2026 accuracy | MathVista accuracy | Video-MME accuracy | GDPval Elo | LiveCodeBench Pass@1 | METR Task-Completion Time Horizons 50% time horizon | SciCode accuracy | MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark) accuracy | AA-Omniscience: Knowledge and Hallucination Benchmark AA-Omniscience Index | IFBench accuracy | MultiChallenge accuracy | OpenAI-MRCR v2 (Multi-Round Coreference Resolution) accuracy (mean SequenceMatcher similarity) | LongBench v2 accuracy | Global-MMLU accuracy | Video-MMMU accuracy | WebDev Arena Elo | Search Arena Elo | Arena-Hard-Auto v2.0 % win rate | EQ-Bench Creative Writing v3 Elo | Design Arena Elo | AILuminate AI Safety Benchmark Safety grade | MASK (Model Alignment between Statements and Knowledge) Honesty score | MCP-Universe Overall Success Rate | CharXiv accuracy | OCRBench v2 accuracy | ScreenSpot-Pro accuracy | FACTS Grounding Grounding accuracy | BigCodeBench calibrated Pass@1 | SWE-bench Multilingual % resolved | SWE-bench Multimodal % resolved | SuperGPQA accuracy | EnigmaEval accuracy | ZeroBench accuracy | IMO-Bench accuracy | PutnamBench Problems solved | MathArena HMMT February 2026 accuracy | FrontierMath Tier 4 accuracy | Vectara Hallucination Leaderboard Hallucination Rate | Gray Swan Arena (Agent Red-Teaming / Indirect Prompt Injection) Attack Success Rate (ASR) | PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts Difficulty-Weighted Accuracy (DW-ACC) | Vibe Code Bench Overall accuracy | Online-Mind2Web Task success rate | WebArena Task success rate | GSO: Software Optimization Benchmark for SWE-Agents Opt@1 | MultiNRC accuracy | Terminal-Bench 2.0 task success | SWE-Marathon resolution rate (pass@1) | FrontierCode weighted score (Diamond) | FrontierSWE dominance score | ProgramBench almost-resolved rate | CursorBench score | PostTrainBench weighted average score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GPT-4o GPT | 31.0% | — | — | 49.2% | 210 | 2.7% | — | — | — | 51.9% | — | — | — | — | 0.34% | 6.4% | — | — | — | 7.2% | — | 17.3 | 129.4 | 23.1% | — | — | — | — | 0.6% | 23.5% | — | 63.8% | 71.9% | 378 | — | 7.0 min | 1.5% | 69.1% | — | — | — | — | 51.4% | — | 61.2% | — | 1006 | — | 1484 | 915 | Good | 60.07 | 15.58% | 58.8% | 47.6 | — | 78.8% | 34.5% | — | 30.37% | 44.40% | 0.80% | 0.0% (pass@1) | — | 1 | — | — | 9.6% | 2.41% | 13.7 | — | 30.7% | 42.8% | 0.0% | 12.42% | — | — | — | — | — | — | — |
| GPT-4.1 GPT | 48.5% | — | — | 66.9% | 606 | — | — | — | 53.96% | — | — | — | — | — | 5.52% | 38.3% | — | — | 39.0% | — | — | 26.3 | 137.6 | 52.4% | — | 80.6% | — | 50.30% | — | 34% | — | 72.2% | — | 776 | 45.7% | — | 38.1% | 74.8% | — | — | 39.43% | — | — | — | — | — | — | 50.0% | 1419 | 1080 | — | 51.13 | 19.91% | 56.7% | — | — | 45.6% | 33.8% | — | 31.14% | — | 2.17% | 0.0% (pass@1) | — | — | — | — | 5.6% | — | 26.4 | — | 36.33% | — | — | 21.23% | — | — | — | — | — | — | — |
| o3 o-series | 62.3% | — | — | 81.8% | 1010 | — | — | — | 63.05% | 76.4% | — | 60.83% | 6.53% | — | 18.69% | 83.9% | 53.0% | — | 52.4% | — | — | 38.4 | 147.3 | 81.3% | — | 85.3% | — | 32.73% | 49.7% | 58.2% | — | 86.8% | — | 753 | 80.8% | 119.7 min | 41.0% | 82.9% | — | 69.3% | 56.62% | — | — | — | 83.3% | — | 1144 | 85.9% | 1744 | 1074 | — | 84.47 | 26.41% | 78.6% | — | — | 36.2% | — | — | 35.98% | — | 13.09% | 3.0% (pass@1) | 61.1% | — | — | 2.1% | — | 2.50% | — | — | 39.00% | — | 8.82% | 45.50% | — | — | — | — | — | — | — |
| o4-mini o-series | — | — | — | 79.6% | 2092 | — | — | — | 53.24% | — | — | 58.67% | 6.11% | — | 24.83% | 81.7% | 23.9% | — | 52.6% | — | — | — | 146.9 | 72.0% | — | 83.2% | — | 36.8% | 28.3% | 42% | — | 84.3% | — | 1008 | 85.9% | — | 46.5% | 81.6% | — | — | 44.90% | — | — | — | — | — | — | 74.6% | — | 1030 | — | 78.60 | 25.97% | 72.0% | — | — | 29.3% | — | — | 33.85% | — | 9.21% | 2.0% (pass@1) | 67.9% | 2 | — | 6.3% | 18.6% | — | 45.6 | — | 32.00% | — | 3.6% | 22.18% | — | — | — | — | — | — | — |
| OpenAI o3-pro OpenAI o-series (o3) | — | — | — | 84% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 40.7 | 148.1 | 84.9% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 62.40% | — | — | — | — | — | — | — | — | — | — | 82.50 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 23.3% | — | — | — | — | — | — | 49.00% | — | — | — | — | — | — | — |
| GPT-OSS-120B GPT OSS | — | — | — | 75.8% | 1299 | — | — | 16.20% | — | — | 1365 | — | — | — | — | 88.9% | 13.9% | — | 48.2% | — | — | 33.3 | 140.8 | 41.8% | — | 80.8% | — | — | — | 65.8% | — | — | — | 947 | 87.8% | — | 38.9% | — | -50 | 69.0% | 45.34% | — | — | 82.8% | — | — | — | — | 1041 | 1017 | — | 92.00 | 25.54% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 14.2% | — | — | — | — | — | — | 15.17% | — | — | — | — | — | — | — |
| GPT-5 GPT | 73.6% | — | — | 86.2% | 2176 | 25.32% | — | 41.78% | — | 78.4% | 1405 | 65.67% | 9.86% | — | 32.41% | 91.4% | 50.6% | — | 60.7% | 44.5% | — | 44.6 | 150.0 | 88.0% | — | 87.1% | — | 42.1% | 54.9% | 96.7% | — | — | — | 1294 | 84.6% | 203.0 min | 42.9% | 84.2% | — | — | 63.19% | — | — | 90.7% | 84.6% | 1394 | 1134 | — | 1640 | 1223 | — | 79.33 | 44.16% | 81.1% | 55.5 | — | 69.6% | — | — | — | — | 10.47% | 1.0% (pass@1) | 65.6% | 28/660 | — | 12.5% | 15.1% | 2.0% | — | 20.09% | 42.33% | — | 6.86% | 52.13% | — | — | — | — | — | — | — |
| GPT-5 mini GPT | 64.7% | — | — | 75.0% | — | 19.4% | — | — | 55.46% | — | — | 54.33% | 4.44% | — | 27.24% | 86.7% | 21.0% | — | 52.7% | — | — | — | 145.6 | — | — | 83.7% | — | 44.8% | — | — | — | — | — | 1184 | 83.8% | — | 41.0% | — | — | — | 58.99% | — | — | 87.4% | — | — | — | — | 1298 | 1170 | — | 82.60 | — | — | — | — | 58.3% | — | 39.7% | — | — | 8.19% | 4.0% (pass@1) | — | — | — | 6.3% | 12.9% | — | — | 14.17% | — | — | — | 23.89% | — | — | — | — | — | — | — |
| GPT-5.1 GPT | 68.0% | — | — | 87.6% | 2269 | 27.2% | — | — | — | 79.0% | 1422 | 72.83% | 17.64% | — | 31.03% | 88.6% | 48.9% | — | 60.8% | — | — | 47.7 | 149.7 | — | — | 87.0% | — | — | — | 95.6% | — | — | — | 1227 | 86.8% | — | 43.3% | 85.4% | — | — | 63.41% | 61.6% | — | 90.6% | — | 1391 | 1199 | — | — | 1216 | — | 86.33 | — | — | — | 3.5% | 50.0% | — | — | — | — | 11.23% | 5.0% (pass@5) | — | — | — | 12.5% | 12.1% | 2.5% | — | 24.61% | — | — | 13.73% | 49.00% | — | — | — | — | — | — | — |
| GPT-5.2 GPT | 73.8% | — | — | 91.4% | 2393 | 29.9% | 74.84% | 29.94% | 55.87% | 80.4% | 1411 | 86.17% | 52.91% | — | 40.7% | 96.1% | 38.9% | — | 72.2% | — | 2.5% | 51.3 | 153.7 | — | — | 85.9% | 47.3% | 40.3% | — | 98.7% | 98.33% | — | — | 1467 | 89.4% | 352.2 min | 46.2% | — | — | — | — | — | — | 89.8% | 85.9% | 1404 | 1210 | — | 1783 | 1224 | — | 86.67 | — | 82.1% | 50.5 | 86.3% | — | — | 66.7% | — | — | 10.39% | 17.0% (pass@5) | — | — | 96.97% | 18.8% | 10.8% | — | — | 53.50% | — | — | 27.45% | 42.18% | — | — | — | — | — | — | 21.38% |
| GPT-5.2-Codex GPT | — | — | — | — | — | — | — | 41.04% | — | — | — | — | — | — | — | — | — | — | — | — | — | 49 | — | — | — | — | — | — | — | — | — | — | — | 1288 | — | — | 54.6% | — | — | — | — | — | — | — | — | 1335 | — | — | — | — | — | — | — | — | — | — | — | — | 66.3% | — | — | — | — | — | — | — | — | — | — | — | 37.91% | — | — | — | — | — | — | — | — | — | — | 17.22% |
| GPT-5.3-Codex GPT | 74.8% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 77.9% | — | — | 53.6 | 155.9 | — | 58.2% | — | 64.7% | — | — | — | — | — | — | 1482 | — | 349.5 min | 53.2% | — | — | — | — | — | — | — | — | 1407 | — | — | — | 1199 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 61.77% | — | — | — | — | 77.3% | — | — | — | — | — | 17.76% |
| GPT-5.4 GPT | 76.9% | — | 55.53% | 93.3% | — | 40.28% | 80.28% | 59.10% | — | 82.1% | 1472 | 93.67% | 73.95% | 0.21% | 47.6% | 95.3% | 44.8% | 31.6% | 77.7% | — | — | 56.8 | 156.1 | — | — | — | 75.0% | 48.2% | — | 87.1% | 99.17% | — | — | 1674 | — | 341.7 min | 56.6% | — | 6 | 73.9% | — | — | — | — | — | 1388 | 1199 | — | 2003 | 1264 | — | 89.67 | — | — | — | 85.4% | — | — | — | — | — | 15.96% | 23.0% (pass@5) | — | — | 97.73% | 27.1% | 7.0% | — | — | 67.42% | 92.8% | — | 31.37% | 58.29% | 75.1% | — | — | 54% | 0.0% | — | 20.23% |
| GPT-5.4 Pro GPT | — | — | — | 94.6% | — | — | — | — | — | — | — | 94.5% | 83.33% | — | 50.0% | — | 47.8% | — | — | — | — | — | 157.7 | — | — | — | — | 50.5% | — | — | — | — | — | — | — | — | — | — | — | — | 69.23% | — | — | — | — | — | — | — | — | — | — | 91.73 | — | — | — | — | — | — | — | — | — | 23.82% | — | — | — | — | 37.5% | 8.3% | — | — | — | — | — | — | 62.27% | — | — | — | — | — | — | — |
| GPT-5.4-mini GPT | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 4.6% | — | — | — | — |
| GPT-5.5 GPT | 80.6% | — | 70.05% | 94.0% | — | 43.56% | 80.71% | 58.6% | — | — | 1468 | 95% | 85% | 0.43% | 51.7% | 100.0% | 63.1% | 53.2% | 84.9% | — | 6.25% | 60 | 158.2 | — | — | — | 78.7% | — | — | 93.9% | 97.50% | — | — | 1769 | — | — | — | — | 20 | 75.9% | — | 74.0% | — | — | — | 1505 | 1239 | — | 2035 | 1301 | — | — | — | 84.1% | — | — | — | — | — | — | — | — | 22.0% (pass@5) | — | — | 97.73% | 35.4% | 9.3% | — | — | 69.85% | — | — | 40.2% | — | — | — | 6.3% | 73% | 13.5% | 64.3% | 25.02% |
| GPT-5.5 Pro GPT | — | — | — | 93.9% | — | — | — | — | — | — | — | 96.5% | 84.58% | — | 52.4% | 100.0% | 64.5% | — | — | — | — | — | 159.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 39.6% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| GPT-5.6 Sol GPT | — | 88.8% | — | 94.6% | — | — | — | 64.6% | — | 83.0% | — | — | — | 7.78% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 90.4% | — | — | — | — | — | — | — | — | — | — | — | — | 73.8% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| GPT-5.6 Sol Ultra GPT | — | 91.9% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 92.2% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| GPT-5.6 Terra GPT | — | 87.4% | — | 92.9% | — | — | — | 63.4% | — | 80.7% | — | — | — | 0.8% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 87.5% | — | — | — | — | — | — | — | — | — | — | — | — | 72.5% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| GPT-5.6 Luna GPT | — | 84.7% | — | 92.3% | — | — | — | 62.7% | — | 78.4% | — | — | — | 0.18% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 83.3% | — | — | — | — | — | — | — | — | — | — | — | — | 41.3% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
Scores are not normalised across benchmarks. Each column uses its own metric. Compare columns independently.