Coding · Alibaba Cloud

QwQ 7B on SWE-bench Verified: score, rank and what it means

QwQ 7B scores 46.4 on SWE-bench Verified, placing it #450 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
46.4
0–100 scale
Rank
#450
of 600
Percentile
25th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
35.3
points

Score distribution

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

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, QwQ 7B sits at #450 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 35.3 points. The median model in this index scores 61.0, which puts QwQ 7B below the midpoint.

Alibaba Cloud models average 60.8 on this benchmark. QwQ 7B is 14.4 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 39.0. QwQ 7B is 7.4 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 46.4 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 SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
ERNIE 4.0 Nano Baidu 32768 $4.68 62.1
Llama 3.3 Groq 8B Groq 16384 $1.17 59.5
Magistral 7B Mistral AI 32768 $1.22 58.9
GPT-NeoX EleutherAI 16384 $1.57 61.7
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
Codestral 8B Mistral AI 4096 $1.18 59.0
MiniMax-Text 8B MiniMax 4096 $1.22 59.5

Other benchmarks for QwQ 7B

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

QwQ 7B scores 46.4 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does QwQ 7B rank on SWE-bench Verified?

It ranks #450 of 600 models, in the 25th percentile. The leader is GPT-5.2 Pro at 81.7.

Is QwQ 7B good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified 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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