Coding · Alibaba Cloud

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

Qwen3-Max Nano scores 74.7 on HumanEval, placing it #349 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
74.7
0–100 scale
Rank
#349
of 600
Percentile
42th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
22.1
points

Score distribution

The chart shows the top 10 models on HumanEval, with Qwen3-Max Nano highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Qwen3-Max Nano sits at #349 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 22.1 points. The median model in this index scores 77.4, which puts Qwen3-Max Nano below the midpoint.

Alibaba Cloud models average 77.1 on this benchmark. Qwen3-Max Nano is 2.4 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.

Among mid-range models, the average is 71.5. Qwen3-Max Nano 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 74.7 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 $8.31 per million input tokens, Qwen3-Max Nano is above the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude Sonnet 4.5 Nano Anthropic 8192 $8.93 72.0
DBRX Instruct Databricks 8192 $3.21 72.4
Mixtral Groq Instruct Groq 16384 $3.25 72.5
OLMo 2 Chat Allen Institute for AI 16384 $2.94 70.6
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
o4 Nano OpenAI 65536 $8.61 72.0
Molmo Instruct Allen Institute for AI 32768 $2.53 68.3

Other benchmarks for Qwen3-Max Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 308 49th
GPQA Diamond 65.0 361 40th
SWE-bench Verified 59.2 339 44th
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 HumanEval?

Qwen3-Max Nano scores 74.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Qwen3-Max Nano rank on HumanEval?

It ranks #349 of 600 models, in the 42nd percentile. The leader is GPT-5.2 Pro at 96.8.

Is Qwen3-Max Nano good at HumanEval?

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 HumanEval score calculated?

HumanEval 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 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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