Reasoning · Alibaba Cloud

Qwen3-Max Nano on GPQA Diamond: score, rank and what it means

Qwen3-Max Nano scores 65.0 on GPQA Diamond, placing it #361 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
65.0
0–100 scale
Rank
#361
of 600
Percentile
40th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
22.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Qwen3-Max Nano 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, Qwen3-Max Nano sits at #361 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 22.0 points. The median model in this index scores 68.8, which puts Qwen3-Max Nano below the midpoint.

Alibaba Cloud models average 67.9 on this benchmark. Qwen3-Max Nano is 2.9 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.

Among mid-range models, the average is 62.9. Qwen3-Max Nano is 2.1 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 65.0 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 $8.31 per million input tokens, Qwen3-Max Nano 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
Nemotron Nano NVIDIA 8192 $2.24 66.6
OLMo 2 Allen Institute for AI 65536 $2.99 71.0
Firesearch Fireworks AI 32768 $7.03 68.5
Grok 3 Nano xAI 8192 $7.12 67.8
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Phi-4 Base Microsoft 32768 $3.15 71.2

Other benchmarks for Qwen3-Max Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 308 49th
SWE-bench Verified 59.2 339 44th
HumanEval 74.7 349 42th
MATH-500 75.6 313 48th
AIME 2025 69.1 280 53th
LiveCodeBench 62.5 343 43th
IFEval 79.3 346 42th
TruthfulQA 76.8 287 52th
HellaSwag 81.9 352 41th
MMMU 68.5 336 44th
Arena Elo 1348.2 368 39th

FAQ

What score does Qwen3-Max Nano get on GPQA Diamond?

Qwen3-Max Nano scores 65.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Qwen3-Max Nano rank on GPQA Diamond?

It ranks #361 of 600 models, in the 40th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Qwen3-Max Nano good at GPQA Diamond?

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 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 Qwen3-Max Nano cost?

Qwen3-Max Nano costs $8.31 per million input tokens and $42.90 per million output tokens.

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