GPT-5.1 leads on the shared-benchmark average
Ahead on 3 of 3 shared benchmarks, averaging 4.9 points higher
Summarised only from the 3 percentage-scale benchmarks scored by every selected model; details are below. A further 1 historical, reverse-direction or differently scaled metrics are excluded; indexes, cost and time are not added to accuracy percentages.
“Best available” takes each model’s best recorded non-parallel result in the metric’s stated direction per benchmark, so it may combine modes into a virtual configuration that does not exist. Read it with the mode breakdown.

Claude Sonnet 4.5
Anthropic
Benchmark-by-benchmark comparison. Changing the thinking mode or tool filters updates the chart and table below.
“Best available” picks the best non-parallel result in the metric’s stated direction separately for each benchmark. The resulting series can combine several reasoning levels and is not one reproducible runtime configuration. Choose a mode filter to compare like-for-like runs.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Each axis is the mean percentage score of one benchmark domain. It is an average, not a capability rating.
Relative edge: Agent能力评测 +8.5 / Relative gap: 多模态理解 -10.1
Relative edge: 多模态理解 +10.1 / Relative gap: Agent能力评测 -8.5
Method: for each model and benchmark, all scores in the current mode scope are averaged (not the best score), then those benchmark scores are averaged within each domain. Only benchmarks scored on a 0-100 scale by at least two of the selected models count — Elo and rating-scale benchmarks such as Codeforces or Arena are excluded, because averaging a 1500 rating with an 85% accuracy produces a meaningless number. Missing values are not counted as zero, and the averages are unweighted, so domains with harder benchmarks read lower.
Every model and runtime mode, benchmark by benchmark. Values are comparable along a row, not between different benchmarks.
29 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | Claude Sonnet 4.5 | GPT-5.1 |
|---|---|---|
63.67Thinking Enabled | 72.83Thinking Level · High | |
13.61Thinking Enabled | 17.64Thinking Level · High | |
1.10Thinking Enabled | 4.90Thinking Level · High | |
33.60Thinking Enabled | Tools | 42.70Thinking Level · High | Tools | |
68.1964K | 72.04Thinking Level · High | |
83.40Thinking Enabled | 88.10Thinking Enabled | |
14.70Standard Mode | Tools | 13.70Thinking Level · High | Tools | |
71.00Thinking Enabled | 86.80Thinking Level · High | |
43.60Thinking Enabled | 50.80Thinking Level · High | |
77.20Thinking Enabled | Tools | 76.30Thinking Level · High | Tools | |
1391.0032K | 1387.00Thinking Level · Medium | |
47.7116K | Tools | 60.77Thinking Level · High | Tools | |
100.00Thinking Enabled | Tools | 94.17Thinking Level · High | Tools | |
5.20Standard Mode | 26.70Thinking Level · High | Tools | |
4.2032K | 12.50Thinking Level · High | Tools | |
4.80Thinking Enabled | 7.10Thinking Enabled | |
59.50Thinking Enabled | Tools | 50.10Thinking Level · High | Tools | |
42.80Thinking Enabled | Tools | 47.60Thinking Level · High | Tools | |
55.80Thinking Enabled | Tools | 52.40Thinking Level · High | Tools | |
77.80Thinking Level · High | 85.40Thinking Level · High | |
68.90Thinking Level · High | 79.00Thinking Enabled | |
39.8032K | 58.70Thinking Level · High | |
54.30Standard Mode | 53.20Thinking Level · High | |
33.00Thinking Enabled | Tools | 45.50Thinking Level · High | Tools | |
98.00Thinking Enabled | Tools | 81.90Thinking Level · High | Tools | |
24.50Thinking Enabled | Tools | 15.90Thinking Level · High | Tools | |
57.30Thinking Enabled | Tools | 72.90Thinking Level · High | |
24.10Thinking Enabled | Tools | 50.80Thinking Level · High | |
72.30Thinking Enabled | 80.00Thinking Level · High |
Official list prices per model API, split by input and output. Unit: USD per 1M tokens.
Architecture, licensing and API modalities. "Not provided" means the field is missing from our database.
| Features & specs | Claude Sonnet 4.5Anthropic | GPT-5.1OpenAI |
|---|---|---|
Core specsRelease | 2025-09-30 | 2025-11-12 |
Context length | 1000K | 400K |
Max output length | 65,536 tokens | 131,072 tokens |
Architecture | Undisclosed | Undisclosed |
Runtime modes | 关闭深度 | 关闭开启 |
Availability & licensingCode availability | Not public | Not public |
Weight availability | Not public | Not public |
Use & commercial terms | Official service only; subject to provider terms | Official service only; subject to provider terms |
API modality supportText Input/Output | Input:YesOutput:Yes | Input:YesOutput:Yes |
Image Input/Output | Input:YesOutput:No | Input:YesOutput:No |
ResourcesPaper / report | Introducing Claude Sonnet 4.5 | GPT-5.1: A smarter, more conversational ChatGPT |
DataLearner blog | 全球最强编程大模型升级:Anthropic发布Claude Sonnet 4.5!同时还有一波重磅工具更新:Claude Code支持保存状态等 | OpenAI发布GPT-5.1:围绕“对话体验、一致性、任务适配性”进行的系统化优化的小幅更新! |

GPT-5.1
OpenAI