Coding · Alibaba Cloud

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

QwQ Instruct scores 67.3 on SWE-bench Verified, placing it #163 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
67.3
0–100 scale
Rank
#163
of 600
Percentile
73th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
14.4
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with QwQ Instruct 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 Instruct sits at #163 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 14.4 points. The median model in this index scores 61.0, which puts QwQ Instruct above the midpoint.

Alibaba Cloud models average 60.8 on this benchmark. QwQ Instruct is 6.5 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.

Among multimodal models, the average is 66.4. QwQ Instruct is 0.9 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 67.3 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 $4.62 per million input tokens, QwQ Instruct is above 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
Reka Core Max Reka AI 128000 $13.41 79.3
Sonar Pro Perplexity 65536 $11.25 77.1
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0
Command A Turbo Cohere 32768 $13.53 79.8
DeepSeek-Coder Instruct DeepSeek 32768 $4.34 77.7

Other benchmarks for QwQ Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.8 189 69th
GPQA Diamond 73.5 187 69th
HumanEval 81.2 210 65th
MATH-500 84.1 124 79th
AIME 2025 74.7 161 73th
LiveCodeBench 72.4 139 77th
IFEval 87.7 110 82th
TruthfulQA 82.8 113 81th
HellaSwag 88.4 128 79th
MMMU 76.8 116 81th
Arena Elo 1420.8 146 76th

FAQ

What score does QwQ Instruct get on SWE-bench Verified?

QwQ Instruct scores 67.3 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does QwQ Instruct rank on SWE-bench Verified?

It ranks #163 of 600 models, in the 73rd percentile. The leader is GPT-5.2 Pro at 81.7.

Is QwQ Instruct good at SWE-bench Verified?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Instruct cost?

QwQ Instruct costs $4.62 per million input tokens and $17.65 per million output tokens.

Related