See key specs and per-benchmark scores for each model/mode. Scroll horizontally for all columns. 当前对比 2 个模型的评测数据与核心参数。
GPT-4
OpenAI
Each axis is a category average, normalized to a 100-point radar.
Relative edge: 编程与软件工程 +17.9 / Relative gap: none clear
Relative edge: none clear / Relative gap: 编程与软件工程 -17.9
Method: for each model and benchmark, the chart first averages all scores in the current mode scope instead of taking the best score, then averages those benchmark scores within each category. Only benchmarks with at least two selected models scored are included; missing values are not counted as zero.
Best overall
Claude3-Opus · 84.93
Best single
Claude3-Opus · MMLU 86.80
Modality coverage
Claude3-Opus · 0 modalities
Head to head
3
Benchmarks
3
Wins
0
Losses
+6.83
Average diff
Compare benchmark results across thinking modes and tool usage.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Complete scores for each model/mode across selected benchmarks.
Side-by-side input/output token pricing
Licensing, MoE architecture, and multi-modality support.
| Features & specs | Claude3-OpusAnthropic | GPT-4OpenAI |
|---|---|---|
Core specsRelease | 2024-03-04 | 2023-03-14 |
Context length | 200K | 128K |
Parameters | — | 1750 |
MoE | No | No |
LicenseCode Open Source | Not provided | Not provided |
Weights Open Source | Not provided | Not provided |
Commercial use | 不开源 | 不开源 |
ResourcesPaper / report | Introducing the next generation of Claude | GPT-4 Technical Report |
DataLearner blog | 评测结果超过GPT-4，Anthropic发布第三代大语言模型Claude3，具有多模态能力，实际评测表现优秀！ | Not provided |
