Commonsense · Alibaba Cloud

QwQ 7B on HellaSwag: score, rank and what it means

QwQ 7B scores 73.5 on HellaSwag, placing it #469 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
73.5
0–100 scale
Rank
#469
of 600
Percentile
22th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
22.6
points

Score distribution

The chart shows the top 10 models on HellaSwag, with QwQ 7B 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, QwQ 7B sits at #469 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 22.6 points. The median model in this index scores 83.6, which puts QwQ 7B below the midpoint.

Alibaba Cloud models average 83.1 on this benchmark. QwQ 7B is 9.6 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 70.2. QwQ 7B is 3.3 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 73.5 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 $1.11 per million input tokens, QwQ 7B is below 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
Yi-Large 8B 01.AI 32768 $0.88 56.1
Llama 3 Anyscale 8B Anyscale 32768 $0.97 57.3
Llama 3 Novita 8B Novita AI 16384 $0.99 55.5
Mistral Small 3 8B Mistral AI 8192 $0.99 57.2
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
GLM-4.5 8B Zhipu AI 32768 $1.46 61.3
GPT-NeoX Chat EleutherAI 16384 $1.49 60.1

Other benchmarks for QwQ 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.9 455 24th
GPQA Diamond 51.2 509 15th
SWE-bench Verified 46.4 450 25th
HumanEval 62.5 463 23th
MATH-500 60.5 455 24th
AIME 2025 49.8 463 23th
LiveCodeBench 44.3 505 16th
IFEval 67.4 497 17th
TruthfulQA 64.7 463 23th
MMMU 54.1 507 16th
Arena Elo 1269.8 460 23th

FAQ

What score does QwQ 7B get on HellaSwag?

QwQ 7B scores 73.5 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does QwQ 7B rank on HellaSwag?

It ranks #469 of 600 models, in the 22nd percentile. The leader is GPT-5.2 Max at 96.1.

Is QwQ 7B 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 QwQ 7B cost?

QwQ 7B costs $1.11 per million input tokens and $5.27 per million output tokens.

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