Yi-Large Base on MATH-500: score, rank and what it means
Yi-Large Base scores 71.2 on MATH-500, placing it #378 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Yi-Large Base highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 2 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 3 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 4 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
| 5 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 6 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 7 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 8 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 9 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 10 | Claude Opus 4.5 Turbo | Anthropic | 2000000 | $19.57 | 85.7 |
What this score means
On MATH-500, Yi-Large Base sits at #378 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 25.5 points. The median model in this index scores 76.0, which puts Yi-Large Base below the midpoint.
01.AI models average 67.4 on this benchmark. Yi-Large Base is 3.8 points above that provider line, so it is a stronger result than the average 01.AI model.
Among open-weight models, the average is 70.8. Yi-Large Base is 0.4 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 71.2 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 $2.78 per million input tokens, Yi-Large Base is below the median input price of $4.00 across the 600 models scored on MATH-500. 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 |
|---|---|---|---|---|
| Arctic Chat | Snowflake | 16384 | $2.70 | 69.8 |
| Auto Pro | OpenRouter | 8192 | $8.41 | 71.2 |
| Firefunction Turbo | Fireworks AI | 32768 | $8.44 | 70.7 |
| Auto Turbo | OpenRouter | 65536 | $7.96 | 70.9 |
| Yi-Large Base | 01.AI | 16384 | $2.78 | 70.3 |
| DBRX Base | Databricks | 32768 | $2.63 | 69.1 |
| Firesearch Reasoning | Fireworks AI | 32768 | $7.74 | 69.0 |
Other benchmarks for Yi-Large Base
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 75.4 | 322 | 46th | |
| GPQA Diamond | 68.0 | 312 | 48th | |
| SWE-bench Verified | 56.8 | 370 | 38th | |
| HumanEval | 73.3 | 369 | 39th | |
| AIME 2025 | 60.4 | 386 | 36th | |
| LiveCodeBench | 60.6 | 361 | 40th | |
| IFEval | 80.4 | 327 | 46th | |
| TruthfulQA | 75.9 | 311 | 48th | |
| HellaSwag | 83.0 | 322 | 46th | |
| MMMU | 68.6 | 333 | 45th | |
| Arena Elo | 1353.7 | 357 | 41th |
FAQ
What score does Yi-Large Base get on MATH-500?
Yi-Large Base scores 71.2 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Yi-Large Base rank on MATH-500?
It ranks #378 of 600 models, in the 37th percentile. The leader is GPT-5.2 Max at 96.7.
Is Yi-Large Base good at MATH-500?
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 MATH-500 score calculated?
MATH-500 is a mathematics 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 Base cost?
Yi-Large Base costs $2.78 per million input tokens and $10.84 per million output tokens.