Yi-Large 7B on MMLU-Pro: score, rank and what it means
Yi-Large 7B scores 61.2 on MMLU-Pro, placing it #510 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.
Score distribution
The chart shows the top 10 models on MMLU-Pro, with Yi-Large 7B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 5 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 6 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 7 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On MMLU-Pro, Yi-Large 7B sits at #510 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 30.4 points. The median model in this index scores 76.1, which puts Yi-Large 7B below the midpoint.
01.AI models average 70.0 on this benchmark. Yi-Large 7B is 8.8 points below that provider line, so it is a weaker result than the average 01.AI model.
Among small open-weight models, the average is 59.8. Yi-Large 7B is 1.4 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 61.2 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $0.83 per million input tokens, Yi-Large 7B is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| DeepSeek-Coder 7B | DeepSeek | 32768 | $1.14 | 57.3 |
| Command R+ 7B | Cohere | 8192 | $0.95 | 56.2 |
| Kimi K1.5 1.5B | Moonshot AI | 4096 | $0.75 | 53.2 |
| Llama 3 Novita 8B | Novita AI | 16384 | $0.99 | 55.5 |
| Yi-Large 7B | 01.AI | 4096 | $0.83 | 55.0 |
| DBRX 8B | Databricks | 4096 | $0.82 | 54.1 |
| Seed-OSS 7B | ByteDance | 8192 | $0.85 | 55.5 |
Other benchmarks for Yi-Large 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 50.0 | 524 | 13th | |
| SWE-bench Verified | 41.6 | 505 | 16th | |
| HumanEval | 60.0 | 505 | 16th | |
| MATH-500 | 57.3 | 496 | 17th | |
| AIME 2025 | 45.9 | 490 | 18th | |
| LiveCodeBench | 42.8 | 520 | 13th | |
| IFEval | 64.9 | 533 | 11th | |
| TruthfulQA | 59.6 | 535 | 11th | |
| HellaSwag | 69.8 | 538 | 10th | |
| MMMU | 51.7 | 537 | 11th | |
| Arena Elo | 1218.0 | 536 | 11th |
FAQ
What score does Yi-Large 7B get on MMLU-Pro?
Yi-Large 7B scores 61.2 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Yi-Large 7B rank on MMLU-Pro?
It ranks #510 of 600 models, in the 15th percentile. The leader is GPT-5.2 Pro at 91.6.
Is Yi-Large 7B good at MMLU-Pro?
It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.
How is the MMLU-Pro score calculated?
MMLU-Pro is a knowledge benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Yi-Large 7B cost?
Yi-Large 7B costs $0.83 per million input tokens and $3.25 per million output tokens.