Model comparison
The Latent benchmark database
Published benchmark results for 31 frontier models, kept in each benchmark's native units and grouped into 7 capability domains.
These results are scattered across lab announcements, leaderboards, and PDFs, and no two of them are reported the same way. This page gathers the benchmarks worth comparing into one table, exactly as their publishers reported them.
17 benchmarks on this page
Knowledge & reasoning
Academic knowledge, mathematics, abstract reasoning, factuality, and long-context reasoning.
| Benchmark | Opus 5.5Anthropic | GPT-6 AstraOpenAI | Gemini 4 ArgonGoogle | Fable 5.1Anthropic | Sonnet 5.5Anthropic | Opus 5Anthropic | MiMo-V2.6-ProXiaomi | Fable 5Anthropic | GPT-6.1 SolOpenAI | GPT-6 SolOpenAI | Muse Spark 1.3Meta | DeepSeek V4.1-FlashDeepSeek | GPT-5.6 SolOpenAI | Grok 4.7xAI | Grok 4.6xAI | Kimi K3Moonshot AI | GLM-5.3Z.ai | Gemini 3.8 FlashGoogle | Gemini 3.7 FlashGoogle | Claude Haiku 5.5Anthropic | GPT-6 LunaOpenAI | GPT-5.6 TerraOpenAI | GLM 5.3 FlashZ.ai | Qwen3.8-MaxAlibaba | Muse Spark 1.2Meta | DeepSeek V4 ProDeepSeek | Mistral Large 4Mistral AI | GPT-5.6 LunaOpenAI | Sonnet 5Anthropic | Qwen3.8-27BAlibaba | DeepSeek V4 FlashDeepSeek | Evidence |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AA-OmniscienceCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | 46.42 | 43.73 | 42.35 | 43.45 | - | 37.07 | 8.38 | 40.15 | 41.53 | 27.12 | 24.93 | - | 21.97 | 32.03 | 30.48 | 19.7 | 14.3 | 29.55 | 26.48 | 10.67 | 0.65 | 0.05 | 7.47 | 3.4 | 27.2 | 0.83 | -5.3 | -10.28 | 16.45 | -7.95 | -14.28 | — |
| ARC-AGI-1Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 98.5% | - | 97.5% | - | 97.5% | - | 98.5% | - | - | - | - | 97.5% | - | 87.5% | 94.5% | - | - | 95.5% | - | - | 96.5% | - | - | - | 90.5% | - | 88% | - | - | 89% | — |
| ARC-AGI-2Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 95% | - | 90% | - | 90.4% | - | 89.2% | - | - | - | - | 92.5% | - | 67.1% | 60.4% | - | - | 84.6% | - | - | 83.9% | - | - | - | 61.3% | - | 59.5% | - | - | 61.4% | SourceCitation |
| ARC-AGI-3 (standard harness)Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 62.71% | - | - | - | 30.16% | - | - | - | - | - | - | 7.78% | - | 2.11% | - | - | - | - | - | - | 0.8% | - | - | - | - | - | 0.18% | - | - | - | — |
| CritPtCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | 31.71% | 31.71% | 27.14% | 29.7% | - | 29.14% | 26.57% | 28.6% | 31.71% | 30.86% | 26% | - | 32.29% | 18% | 19.71% | 23.43% | 19.14% | 18.29% | 14.29% | 22.57% | 19.43% | 30% | 15.43% | 20% | 17.71% | 18% | 10.57% | 20.57% | 16.86% | 5.43% | 16.57% | — |
| FrontierMath v2 Tier 4Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 97.56% | - | 87.8% | - | 73.17% | - | 87.8% | - | - | - | - | 82.93% | - | - | 39.02% | 29.27% | - | 36.59% | - | - | 70.73% | - | 46.3% | - | 26.83% | - | 60.98% | 29.27% | - | 24.4% | — |
| GPQA DiamondCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 96.26% | - | 93.74% | - | 93.74% | - | 92.6% | - | - | 94.14% | 90.9% | 94.14% | - | 94.95% | 93.54% | 91.72% | 95.25% | 94.55% | - | - | 92.53% | - | 92.73% | 90.4% | 92.83% | - | 91.11% | 91.11% | 90.51% | 91.31% | SourceCitation |
| Humanity's Last Exam (no tools)Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | 64.4% | 54.68% | - | 59.13% | 56.9% | 54.87% | 49.35% | 53.3% | - | - | 49.07% | 36.8% | 49.49% | 43.14% | 44.07% | 46.9% | 42.26% | 47.82% | 47.87% | 45.9% | - | 42.91% | - | 43.05% | 45.46% | 41.01% | - | 39.48% | 41.29% | 33.92% | 38.55% | — |
| LiveBenchCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 82.16% | - | 83.41% | - | 80.08% | - | 82.97% | - | - | 81.59% | - | 81.05% | - | 78.04% | 79.19% | 76.14% | 75.83% | 78.8% | - | - | 77.94% | - | 78.5% | 78% | 77.44% | - | 73.56% | 76.04% | 75.27% | 74.17% | SourceCitation |
| MathArena - ArXivLean Jun 2026Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 63.83% | - | - | - | 31.25% | - | 14.58% | - | - | - | - | 37.5% | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | — |
| MathArena - ArXivMath Jun 2026Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 94.44% | - | 90.97% | - | 80.95% | - | 83.67% | - | - | - | - | 86.73% | - | - | 72.11% | - | 68.03% | 63.27% | - | - | - | - | - | - | - | - | - | - | - | 42.86% | — |
| MathArena - ArXivMath May 2026Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 95% | - | 87.5% | - | - | - | 87.5% | - | - | - | - | - | - | - | 61.67% | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 55.83% | — |
| MathArena - BrokenArXiv Jun 2026Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 99.07% | - | 84.72% | - | 90.74% | - | 47.84% | - | - | - | - | 67.28% | - | - | 51.85% | - | 20.83% | 11.11% | - | - | - | - | - | - | - | - | - | - | - | 16.67% | — |
| MLCR-AA (Medical Long Context Reasoning)Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 35% | - | 71.11% | - | 59.44% | - | 64.44% | - | - | - | - | 26.11% | - | 12.22% | 38.33% | 48.33% | - | 15% | - | - | 31.67% | - | 19.44% | 31.11% | 17.78% | - | 19.44% | 55% | 21.67% | 13.33% | — |
| MMLU Pro - ValsCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | - | - | 92.38% | - | 91.59% | - | 91.5% | - | - | - | - | 89.1% | - | 89.4% | 87.97% | 86.77% | 90.22% | 90.12% | - | - | 86.66% | - | 88.6% | 88.28% | 86.97% | - | 86.04% | 87.55% | 84.34% | 86.21% | — |
| Mystery Game Puzzles v1.0.4 - EpochCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 84% | - | 58% | - | 59% | - | 52% | - | - | - | - | 58% | - | - | 26% | 33% | - | 37% | - | - | 35% | - | - | - | 43% | - | 21% | 35% | - | 34% | — |
| ProofBench v1.1 - ValsCurrent values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 99% | - | 100% | - | 99% | - | 95% | - | - | - | - | 83% | - | 51% | 87% | 49% | 48% | 58% | - | - | 74% | - | 58% | 43% | 50% | - | 60% | 77% | 16% | 56% | — |
3 benchmarks on this page
Coding & software engineering
Agentic terminal work, issue resolution, long-horizon engineering, competitive coding, and autonomous ML engineering.
| Benchmark | Opus 5.5Anthropic | GPT-6 AstraOpenAI | Gemini 4 ArgonGoogle | Fable 5.1Anthropic | Sonnet 5.5Anthropic | Opus 5Anthropic | MiMo-V2.6-ProXiaomi | Fable 5Anthropic | GPT-6.1 SolOpenAI | GPT-6 SolOpenAI | Muse Spark 1.3Meta | DeepSeek V4.1-FlashDeepSeek | GPT-5.6 SolOpenAI | Grok 4.7xAI | Grok 4.6xAI | Kimi K3Moonshot AI | GLM-5.3Z.ai | Gemini 3.8 FlashGoogle | Gemini 3.7 FlashGoogle | Claude Haiku 5.5Anthropic | GPT-6 LunaOpenAI | GPT-5.6 TerraOpenAI | GLM 5.3 FlashZ.ai | Qwen3.8-MaxAlibaba | Muse Spark 1.2Meta | DeepSeek V4 ProDeepSeek | Mistral Large 4Mistral AI | GPT-5.6 LunaOpenAI | Sonnet 5Anthropic | Qwen3.8-27BAlibaba | DeepSeek V4 FlashDeepSeek | Evidence |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| APEX-SWE (Pass@1, Terminus-2)Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | - | - | 63.6% | - | 63.7% | - | 58.8% | - | - | - | - | 45.8% | - | 56.4% | 48% | - | - | - | - | - | - | - | - | - | - | - | - | 46.4% | - | 46.9% | — |
| Code Arena WebDev (overall)Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 1,797 | - | 1,762 | - | 1,688 | - | 1,629 | - | - | 1,622 | - | 1,617 | - | 1,625 | 1,674 | 1,609 | 1,567 | 1,587 | - | - | 1,520 | - | 1,670 | 1,534 | - | - | 1,519 | 1,537 | 1,594 | - | — |
| Code Migration †Current values follow the best-published-reasoning-mode policy. Individual source, configuration and admission decisions are disclosed on /methodology#model-evidence. Collected values without a matching review remain visible but do not contribute. | - | 67.74% | - | 54.61% | - | 57.47% | - | 55.06% | - | - | - | - | 52.92% | - | 44.57% | 16.1% | 44.22% | 36.55% | 34.8% | - | - | 47.8% | - | 23.96% | 29.95% | 41.54% | - | 44.55% | 44.39% | 14.16% | 38.63% | SourceCitation |
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Reading this table
Native units, nothing adjusted
Units
Cells show each benchmark's native scale: accuracy percentages, Elo ratings, or points. Nothing is rescaled or converted, so compare along a row. Two different rows are two different scales.
Best in row
The strongest published result in each row is highlighted. A blank cell means that model has no published result on that benchmark, which is not the same as a zero.
What gets listed
A benchmark earns a row when its result is published against a named model version with a stated metric, and when enough models have run it for the comparison to mean something. Numbers we cannot trace back to a source are left out.
Provenance
Results are current as of 2026-10-10. Vendor-reported head-to-head rows are named as such (e.g. “Anthropic H2H”) and carry their caveats in the row notes.
Evidence downloads: manifest · dataset JSON · results CSV · citations CSV