Claude Sonnet 4.6 leads on the shared-benchmark average
Ahead on 1 of 1 shared benchmarks, averaging 0.7 points higher
Summarised only from the 1 percentage-scale benchmarks scored by every selected model; details are below. A further 2 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 4.6
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: AI Agent - 信息收集 +8.9 / Relative gap: 数学推理 -6.7
Relative edge: 数学推理 +6.7 / Relative gap: AI Agent - 信息收集 -8.9
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.
13 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | Claude Sonnet 4.6 | GPT-5.2 |
|---|---|---|
86.50Thinking Level · High | Tools | 86.17Thinking Level · Extra High | |
60.42Thinking Level · High | Tools | 52.91Thinking Level · Extra High | |
49.00Thinking Enabled | Tools | 45.50Deep Thinking Mode | Tools | |
75.32Thinking Level · High | 74.63Thinking Level · High | |
89.90Thinking Enabled | 92.40Thinking Level · Extra High | |
79.60Thinking Enabled | 80.00Thinking Level · Extra High | Tools | |
1804.20Standard Mode | 1699.80Standard Mode | |
8.3016K | 18.80Thinking Level · Extra High | |
97.90Thinking Enabled | Tools | 98.70Thinking Level · Extra High | Tools | |
74.70Thinking Enabled | Tools | 65.80Thinking Level · Extra High | Tools | |
69.50Standard Mode | Tools | 67.60Thinking Level · Extra High | Tools | |
57.00Thinking Enabled | 70.90Thinking Level · High | Tools | |
80.00Thinking Enabled | 82.70Thinking Level · Extra 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 4.6Anthropic | GPT-5.2OpenAI |
|---|---|---|
Core specsRelease | 2026-02-17 | 2025-12-11 |
Context length | 1M | 400K |
Max output length | 8,192 tokens | Not provided |
Architecture | Undisclosed | Undisclosed |
Runtime modes | 关闭开启深度 | 低中高极高 |
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 4.6 | Introducing GPT-5.2 |

GPT-5.2
OpenAI