SciAgentBench - Physics: leaderboard

Metric: Success rate (%, 0-100) on the 109 physics tasks; with tools: a ReAct loop over the task-relevant SciAgentGym tools (native function calling, up to 50 tool rounds, 300-second request timeout); SciAgentBench: 259 multi-step scientific tasks (1,134 sub-questions; physics 109, chemistry 81, materials 37, life sciences 32; about 65 percent with images) aggregated from existing benchmarks, kept when four frontier LLMs averaged under 50 percent and SciAgentGym could execute a verified trace; a task counts only when every sub-question is correct (strict JSON matching with 0.05 numeric tolerance, GPT-4.1 checking textual fields); temperature 0.7; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 17 models tracked.

Top models

#ModelScoreOverall rank
1Grok 4.147.2#218
2GPT-546.3#91
3Claude Sonnet 439.4#194
4Gemini 2.5 Flash38.3#237
5Gemini 2.5 Pro37.3#145
6O335.5#121
7Qwen 3 VL 32B (Thinking)33#287 (Qwen 3 VL 32B)
8Qwen 3 VL 32B Instruct31.8#276
9O4 Mini31.2#172
10GLM-4.6V30.9#309
11Qwen 3 VL 235B A22B (Thinking)30.6#228 (Qwen 3 VL 235B A22B)
12Qwen 3 VL 235B A22B Instruct28.1#264
13Qwen 3 VL 8B Instruct24#401
14Qwen 3 VL 4B Instruct23.8#506
15GPT-4o21.3#333

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=sciagentbench-physics · How It Works · Data refreshed daily, snapshot 2026-10-11.