Reasoning · Alibaba Cloud

QwQ on GPQA Diamond: score, rank and what it means

QwQ scores 76.7 on GPQA Diamond, placing it #108 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
76.7
0–100 scale
Rank
#108
of 600
Percentile
82th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
10.3
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with QwQ highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, QwQ sits at #108 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 10.3 points. The median model in this index scores 68.8, which puts QwQ above the midpoint.

Alibaba Cloud models average 67.9 on this benchmark. QwQ is 8.8 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.

Among multimodal models, the average is 73.5. QwQ is 3.2 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 76.7 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 $4.57 per million input tokens, QwQ is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 4 Scout Chat Meta AI 32768 $4.66 78.0
Sonar Pro Perplexity 128000 $13.01 79.1
Claude 3.7 Sonnet Max Anthropic 128000 $16.88 83.7
Llama 4 Maverick Meta AI 200000 $5.36 81.6
QwQ Alibaba Cloud 128000 $4.57 78.6
Gemini 2.5 Pro Google DeepMind 200000 $15.20 81.6
ERNIE 4.0 Max Baidu 32768 $12.40 78.9

Other benchmarks for QwQ

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.3 234 61th
SWE-bench Verified 68.3 138 77th
HumanEval 84.4 126 79th
MATH-500 80.0 208 65th
AIME 2025 78.8 104 83th
LiveCodeBench 71.2 164 73th
IFEval 84.3 207 66th
TruthfulQA 79.9 184 69th
HellaSwag 88.0 141 77th
MMMU 75.0 163 73th
Arena Elo 1415.0 167 72th

FAQ

What score does QwQ get on GPQA Diamond?

QwQ scores 76.7 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does QwQ rank on GPQA Diamond?

It ranks #108 of 600 models, in the 82nd percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is QwQ good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 cost?

QwQ costs $4.57 per million input tokens and $16.94 per million output tokens.

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