Mathematics · Alibaba Cloud

QwQ 8B on MATH-500: score, rank and what it means

QwQ 8B scores 60.4 on MATH-500, placing it #456 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
60.4
0–100 scale
Rank
#456
of 600
Percentile
24th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
36.3
points

Score distribution

The chart shows the top 10 models on MATH-500, with QwQ 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, QwQ 8B sits at #456 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 36.3 points. The median model in this index scores 76.0, which puts QwQ 8B below the midpoint.

Alibaba Cloud models average 76.4 on this benchmark. QwQ 8B is 16.0 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 53.7. QwQ 8B is 6.7 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 60.4 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 $1.37 per million input tokens, QwQ 8B is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mistral Large 3 8B Mistral AI 16384 $1.62 61.6
Qwen3 7B Alibaba Cloud 32768 $1.37 59.8
Nova Lite Nano Amazon 8192 $3.29 59.5
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
QwQ 8B Alibaba Cloud 16384 $1.37 59.5
Llama 3.1 Cerebras 8B Cerebras 32768 $1.02 58.2
MiniMax-M2 7B MiniMax 8192 $1.44 60.8

Other benchmarks for QwQ 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.6 460 23th
GPQA Diamond 55.7 454 24th
SWE-bench Verified 47.3 443 26th
HumanEval 64.2 451 25th
AIME 2025 47.0 477 21th
LiveCodeBench 49.0 456 24th
IFEval 71.3 436 27th
TruthfulQA 63.7 478 20th
HellaSwag 73.0 483 20th
MMMU 58.5 450 25th
Arena Elo 1287.7 434 28th

FAQ

What score does QwQ 8B get on MATH-500?

QwQ 8B scores 60.4 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does QwQ 8B rank on MATH-500?

It ranks #456 of 600 models, in the 24th percentile. The leader is GPT-5.2 Max at 96.7.

Is QwQ 8B good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 8B cost?

QwQ 8B costs $1.37 per million input tokens and $6.68 per million output tokens.

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