DeepSeek-Coder 7B on MMMU: score, rank and what it means
DeepSeek-Coder 7B scores 53.2 on MMMU, placing it #517 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 DeepSeek-Coder 7B 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, DeepSeek-Coder 7B sits at #517 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 33.7 points. The median model in this index scores 70.0, which puts DeepSeek-Coder 7B below the midpoint.
DeepSeek models average 68.9 on this benchmark. DeepSeek-Coder 7B is 15.7 points below that provider line, so it is a weaker result than the average DeepSeek model.
Among coding models, the average is 66.1. DeepSeek-Coder 7B is 12.9 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 53.2 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 $1.14 per million input tokens, DeepSeek-Coder 7B 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 |
|---|---|---|---|---|
| GLM-4.6 1.5B | Zhipu AI | 4096 | $0.92 | 54.7 |
| Mixtral Turbo 8B | Together AI | 4096 | $0.75 | 54.1 |
| MiniMax-Text 7B | MiniMax | 16384 | $1.10 | 57.7 |
| Command R+ 7B | Cohere | 8192 | $0.95 | 56.2 |
| DeepSeek-Coder 7B | DeepSeek | 32768 | $1.14 | 57.3 |
| Gemma 3 8B | Google DeepMind | 16384 | $0.96 | 56.5 |
| Llama 3 DeepInfra 7B | DeepInfra | 16384 | $0.95 | 55.6 |
Other benchmarks for DeepSeek-Coder 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 61.7 | 506 | 16th | |
| GPQA Diamond | 54.1 | 478 | 20th | |
| SWE-bench Verified | 43.6 | 483 | 20th | |
| HumanEval | 62.0 | 468 | 22th | |
| MATH-500 | 56.9 | 498 | 17th | |
| AIME 2025 | 43.8 | 511 | 15th | |
| LiveCodeBench | 48.3 | 462 | 23th | |
| IFEval | 70.1 | 459 | 24th | |
| TruthfulQA | 63.8 | 471 | 22th | |
| HellaSwag | 73.2 | 474 | 21th | |
| Arena Elo | 1260.7 | 473 | 21th |
FAQ
What score does DeepSeek-Coder 7B get on MMMU?
DeepSeek-Coder 7B scores 53.2 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does DeepSeek-Coder 7B rank on MMMU?
It ranks #517 of 600 models, in the 14th percentile. The leader is GPT-5.2 Max at 86.9.
Is DeepSeek-Coder 7B 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 DeepSeek-Coder 7B cost?
DeepSeek-Coder 7B costs $1.14 per million input tokens and $4.37 per million output tokens.