Coding · Alibaba Cloud

QwQ 7B on HumanEval: score, rank and what it means

QwQ 7B scores 62.5 on HumanEval, placing it #463 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
62.5
0–100 scale
Rank
#463
of 600
Percentile
23th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
34.3
points

Score distribution

The chart shows the top 10 models on HumanEval, with QwQ 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, QwQ 7B sits at #463 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 34.3 points. The median model in this index scores 77.4, which puts QwQ 7B below the midpoint.

Alibaba Cloud models average 77.1 on this benchmark. QwQ 7B is 14.6 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 56.7. QwQ 7B is 5.8 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 62.5 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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Codestral 8B Mistral AI 4096 $1.18 59.0
Pythia EleutherAI 32768 $1.29 59.8
Auto Nano OpenRouter 4096 $2.83 57.1
Kimi K2 1.5B Moonshot AI 4096 $0.99 56.8
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
Firefunction Nano Fireworks AI 16384 $3.07 58.1
Codestral 7B Mistral AI 32768 $1.05 57.0

Other benchmarks for QwQ 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.9 455 24th
GPQA Diamond 51.2 509 15th
SWE-bench Verified 46.4 450 25th
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 HumanEval?

QwQ 7B scores 62.5 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does QwQ 7B rank on HumanEval?

It ranks #463 of 600 models, in the 23rd percentile. The leader is GPT-5.2 Pro at 96.8.

Is QwQ 7B good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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.

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