Yi-Large Chat on MMLU-Pro: score, rank and what it means
Yi-Large Chat scores 75.7 on MMLU-Pro, placing it #314 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 Chat 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 Chat sits at #314 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 15.9 points. The median model in this index scores 76.1, which puts Yi-Large Chat below the midpoint.
01.AI models average 70.0 on this benchmark. Yi-Large Chat is 5.7 points above that provider line, so it is a stronger result than the average 01.AI model.
Among multimodal models, the average is 80.0. Yi-Large Chat is 4.3 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 75.7 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 $3.49 per million input tokens, Yi-Large Chat 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 |
|---|---|---|---|---|
| Llama 3.1 Turbo Base | Together AI | 16384 | $3.30 | 73.0 |
| Seed-OSS Base | ByteDance | 16384 | $3.14 | 72.2 |
| Fusion Pro | OpenRouter | 65536 | $8.69 | 72.2 |
| Mixtral Base | Mistral AI | 65536 | $2.95 | 71.1 |
| Yi-Large Chat | 01.AI | 65536 | $3.49 | 73.5 |
| Firefunction Pro | Fireworks AI | 16384 | $9.05 | 72.9 |
| Llama 3 DeepInfra Base | DeepInfra | 16384 | $2.95 | 71.8 |
Other benchmarks for Yi-Large Chat
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 69.0 | 297 | 51th | |
| SWE-bench Verified | 59.3 | 338 | 44th | |
| HumanEval | 79.5 | 249 | 59th | |
| MATH-500 | 76.1 | 297 | 51th | |
| AIME 2025 | 71.0 | 238 | 60th | |
| LiveCodeBench | 62.7 | 339 | 44th | |
| IFEval | 82.4 | 262 | 56th | |
| TruthfulQA | 78.4 | 242 | 60th | |
| HellaSwag | 82.9 | 324 | 46th | |
| MMMU | 71.2 | 269 | 55th | |
| Arena Elo | 1386.2 | 262 | 56th |
FAQ
What score does Yi-Large Chat get on MMLU-Pro?
Yi-Large Chat scores 75.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Yi-Large Chat rank on MMLU-Pro?
It ranks #314 of 600 models, in the 48th percentile. The leader is GPT-5.2 Pro at 91.6.
Is Yi-Large Chat 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 Chat cost?
Yi-Large Chat costs $3.49 per million input tokens and $13.97 per million output tokens.