QwQ 7B on MMLU-Pro: score, rank and what it means
QwQ 7B scores 64.9 on MMLU-Pro, placing it #455 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 QwQ 7B 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, QwQ 7B sits at #455 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 26.7 points. The median model in this index scores 76.1, which puts QwQ 7B below the midpoint.
Alibaba Cloud models average 75.9 on this benchmark. QwQ 7B is 11.0 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.
Among small open-weight models, the average is 59.8. QwQ 7B is 5.1 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 64.9 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 $1.11 per million input tokens, QwQ 7B 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 4 Maverick 7B | Meta AI | 4096 | $1.52 | 61.9 |
| GLM-4.5 7B | Zhipu AI | 8192 | $1.32 | 60.2 |
| Auto Nano | OpenRouter | 4096 | $2.83 | 57.1 |
| Llama 3 DeepInfra 8B | DeepInfra | 8192 | $1.05 | 57.4 |
| QwQ 7B | Alibaba Cloud | 8192 | $1.11 | 58.1 |
| Llama 3.1 7B | Meta AI | 8192 | $1.01 | 57.4 |
| Magistral 8B | Mistral AI | 4096 | $1.33 | 60.0 |
Other benchmarks for QwQ 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 51.2 | 509 | 15th | |
| SWE-bench Verified | 46.4 | 450 | 25th | |
| HumanEval | 62.5 | 463 | 23th | |
| MATH-500 | 60.5 | 455 | 24th | |
| AIME 2025 | 49.8 | 463 | 23th | |
| LiveCodeBench | 44.3 | 505 | 16th | |
| IFEval | 67.4 | 497 | 17th | |
| TruthfulQA | 64.7 | 463 | 23th | |
| HellaSwag | 73.5 | 469 | 22th | |
| MMMU | 54.1 | 507 | 16th | |
| Arena Elo | 1269.8 | 460 | 23th |
FAQ
What score does QwQ 7B get on MMLU-Pro?
QwQ 7B scores 64.9 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does QwQ 7B rank on MMLU-Pro?
It ranks #455 of 600 models, in the 24th percentile. The leader is GPT-5.2 Pro at 91.6.
Is QwQ 7B 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 QwQ 7B cost?
QwQ 7B costs $1.11 per million input tokens and $5.27 per million output tokens.