Commonsense · Alibaba Cloud

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

Qwen3-Max Nano scores 81.9 on HellaSwag, placing it #352 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
81.9
0–100 scale
Rank
#352
of 600
Percentile
41th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
14.2
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Qwen3-Max Nano sits at #352 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 14.2 points. The median model in this index scores 83.6, which puts Qwen3-Max Nano below the midpoint.

Alibaba Cloud models average 83.1 on this benchmark. Qwen3-Max Nano is 1.2 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.

Among mid-range models, the average is 79.8. 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 81.9 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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Firefunction Turbo Fireworks AI 32768 $8.44 70.7
Gemini 3 Pro Nano Google DeepMind 8192 $9.11 73.2
Llama 3.1 Base Meta AI 32768 $3.39 72.2
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Yi-Lightning Base 01.AI 16384 $3.31 72.7
Firesearch Reasoning Fireworks AI 32768 $7.74 69.0

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
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
MMMU 68.5 336 44th
Arena Elo 1348.2 368 39th

FAQ

What score does Qwen3-Max Nano get on HellaSwag?

Qwen3-Max Nano scores 81.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Qwen3-Max Nano rank on HellaSwag?

It ranks #352 of 600 models, in the 41st percentile. The leader is GPT-5.2 Max at 96.1.

Is Qwen3-Max Nano good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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