Reasoning · Alibaba Cloud

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

QwQ Chat scores 72.8 on GPQA Diamond, placing it #203 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
72.8
0–100 scale
Rank
#203
of 600
Percentile
66th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
14.2
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with QwQ Chat 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 Chat sits at #203 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 14.2 points. The median model in this index scores 68.8, which puts QwQ Chat above the midpoint.

Alibaba Cloud models average 67.9 on this benchmark. QwQ Chat is 4.9 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 Chat is 0.7 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 72.8 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 $4.28 per million input tokens, QwQ Chat 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 Maverick Chat Meta AI 128000 $5.09 79.7
Yi-Lightning Instruct 01.AI 128000 $4.16 76.5
GLM-4.6 Chat Zhipu AI 400000 $4.89 79.8
MiniMax-Text Instruct MiniMax 128000 $4.59 77.7
QwQ Chat Alibaba Cloud 65536 $4.28 78.2
Llama 3 Hyperbolic Chat Hyperbolic 200000 $3.64 75.1
Llama 3 Replicate Instruct Replicate 128000 $3.71 75.1

Other benchmarks for QwQ Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.6 167 72th
SWE-bench Verified 68.3 139 77th
HumanEval 83.4 151 75th
MATH-500 82.1 166 72th
AIME 2025 76.1 140 77th
LiveCodeBench 68.8 213 65th
IFEval 85.2 186 69th
TruthfulQA 79.8 191 68th
HellaSwag 87.9 147 76th
MMMU 75.7 145 76th
Arena Elo 1414.1 173 71th

FAQ

What score does QwQ Chat get on GPQA Diamond?

QwQ Chat scores 72.8 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does QwQ Chat rank on GPQA Diamond?

It ranks #203 of 600 models, in the 66th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is QwQ Chat 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 Chat cost?

QwQ Chat costs $4.28 per million input tokens and $16.00 per million output tokens.

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