Mistral Small 3 1.5B on MMMU: score, rank and what it means
Mistral Small 3 1.5B scores 48.0 on MMMU, placing it #565 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.
Score distribution
The chart shows the top 10 models on MMMU, with Mistral Small 3 1.5B 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-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 4 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 5 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 6 | Grok 4 Pro | xAI | 1000000 | $19.00 | 85.4 |
| 7 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 8 | Claude Sonnet 4.5 Pro | Anthropic | 1000000 | $18.73 | 86.7 |
| 9 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 10 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
What this score means
On MMMU, Mistral Small 3 1.5B sits at #565 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 38.9 points. The median model in this index scores 70.0, which puts Mistral Small 3 1.5B below the midpoint.
Mistral AI models average 64.8 on this benchmark. Mistral Small 3 1.5B is 16.8 points below that provider line, so it is a weaker result than the average Mistral AI model.
Among small open-weight models, the average is 52.4. Mistral Small 3 1.5B is 4.4 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 48.0 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 $0.42 per million input tokens, Mistral Small 3 1.5B is below the median input price of $4.00 across the 600 models scored on MMMU. 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 |
|---|---|---|---|---|
| Gemma 3 1.5B | Google DeepMind | 32768 | $0.40 | 48.9 |
| DBRX 7B | Databricks | 8192 | $0.65 | 51.9 |
| DBRX 1.5B | Databricks | 16384 | $0.32 | 47.0 |
| Llama 3.1 Cerebras 1.5B | Cerebras | 4096 | $0.48 | 50.2 |
| Mistral Small 3 1.5B | Mistral AI | 32768 | $0.42 | 49.2 |
| StableLM 2 8B | Stability AI | 32768 | $0.38 | 47.0 |
| Mixtral 1.5B | Mistral AI | 16384 | $0.36 | 47.7 |
Other benchmarks for Mistral Small 3 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 56.3 | 566 | 6th | |
| GPQA Diamond | 44.3 | 569 | 5th | |
| SWE-bench Verified | 34.7 | 561 | 7th | |
| HumanEval | 50.9 | 568 | 5th | |
| MATH-500 | 48.7 | 569 | 5th | |
| AIME 2025 | 36.6 | 558 | 7th | |
| LiveCodeBench | 34.5 | 572 | 5th | |
| IFEval | 62.5 | 551 | 8th | |
| TruthfulQA | 56.1 | 564 | 6th | |
| HellaSwag | 68.5 | 554 | 8th | |
| Arena Elo | 1200.3 | 555 | 8th |
FAQ
What score does Mistral Small 3 1.5B get on MMMU?
Mistral Small 3 1.5B scores 48.0 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Mistral Small 3 1.5B rank on MMMU?
It ranks #565 of 600 models, in the 6th percentile. The leader is GPT-5.2 Max at 86.9.
Is Mistral Small 3 1.5B good at MMMU?
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 MMMU score calculated?
MMMU is a multimodal 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 Mistral Small 3 1.5B cost?
Mistral Small 3 1.5B costs $0.42 per million input tokens and $1.58 per million output tokens.