Qwen3-Coder 1.5B on MMMU: score, rank and what it means
Qwen3-Coder 1.5B scores 53.0 on MMMU, placing it #520 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 Qwen3-Coder 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, Qwen3-Coder 1.5B sits at #520 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 33.9 points. The median model in this index scores 70.0, which puts Qwen3-Coder 1.5B below the midpoint.
Alibaba Cloud models average 69.4 on this benchmark. Qwen3-Coder 1.5B is 16.4 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.
Among coding models, the average is 66.1. Qwen3-Coder 1.5B is 13.1 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 53.0 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 $0.76 per million input tokens, Qwen3-Coder 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 |
|---|---|---|---|---|
| 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 |
| Qwen3-Coder 1.5B | Alibaba Cloud | 32768 | $0.76 | 52.8 |
| Pythia Base | EleutherAI | 16384 | $0.99 | 55.9 |
| GLM-4.5 1.5B | Zhipu AI | 16384 | $0.65 | 53.3 |
Other benchmarks for Qwen3-Coder 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 57.8 | 552 | 8th | |
| GPQA Diamond | 46.7 | 552 | 8th | |
| SWE-bench Verified | 37.0 | 541 | 10th | |
| HumanEval | 58.6 | 517 | 14th | |
| MATH-500 | 51.9 | 541 | 10th | |
| AIME 2025 | 43.2 | 521 | 13th | |
| LiveCodeBench | 40.8 | 533 | 11th | |
| IFEval | 63.8 | 540 | 10th | |
| TruthfulQA | 59.9 | 532 | 11th | |
| HellaSwag | 68.5 | 555 | 8th | |
| Arena Elo | 1215.0 | 538 | 10th |
FAQ
What score does Qwen3-Coder 1.5B get on MMMU?
Qwen3-Coder 1.5B scores 53.0 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Qwen3-Coder 1.5B rank on MMMU?
It ranks #520 of 600 models, in the 13th percentile. The leader is GPT-5.2 Max at 86.9.
Is Qwen3-Coder 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 Qwen3-Coder 1.5B cost?
Qwen3-Coder 1.5B costs $0.76 per million input tokens and $2.67 per million output tokens.