Coding
Writing and editing code against a specification, measured without an agent loop. Distinct from agentic coding: these benchmarks score the model's output directly rather than a model-plus-harness system. Ordered by how many of these benchmarks put a model in their top 10, then by its best placing. Each column keeps its own ranking; nothing is averaged. A dash means the board does not list that model — not a score of zero. Entries not yet matched to a model are left out here; they still appear on their own board.
| Model | In top 10 | Artificial Analysis LLM Leaderboard SciCode | Arena — Code Overall |
|---|---|---|---|
 Claude Opus 5.5 Anthropic | 2/2 | #1 66.9% | #1 1813 |
| Claude Fable 5.1 Anthropic | 2/2 | #2 63.1% | #5 1744 |
 Gemini 4 Argon Google | 2/2 | #3 61.8% | #8 1678 |
| Claude Sonnet 5.5 Anthropic | 2/2 | #5 61.0% | #3 1774 |
 Muse Spark 1.3 Meta | 2/2 | #8 59.7% | #10 1657 |
 GPT 6 Astra OpenAI | 1/2 | #19 56.5% | #2 1786 |
| Claude Fable 5 Anthropic | 1/2 | #4 61.0% | #17 1625 |
| GPT 6.1 Sol OpenAI | 1/2 | #23 55.8% | #4 1755 |
 MiMo V2.6 Pro Xiaomi | 1/2 | #6 60.9% | #16 1629 |
| Claude Opus 5 Anthropic | 1/2 | #21 56.4% | #6 1691 |
| Gemini 3.7 Flash Google | 1/2 | #7 59.8% | #25 1592 |
| GPT 6 Sol OpenAI | 1/2 | #16 57.6% | #7 1688 |
 Kimi K3 Kimi | 1/2 | #9 59.5% | #11 1654 |
 Qwen 3.8 Max Alibaba | 1/2 | #32 54.1% | #9 1674 |
 GLM 5.3 Z AI | 1/2 | #10 59.0% | #18 1622 |