Commonsense · Alibaba Cloud

QwQ Base on HellaSwag: score, rank and what it means

QwQ Base scores 86.4 on HellaSwag, placing it #201 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
86.4
0–100 scale
Rank
#201
of 600
Percentile
67th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
9.7
points

Score distribution

The chart shows the top 10 models on HellaSwag, with QwQ Base 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 Base sits at #201 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 9.7 points. The median model in this index scores 83.6, which puts QwQ Base above the midpoint.

Alibaba Cloud models average 83.1 on this benchmark. QwQ Base is 3.3 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.

Among multimodal models, the average is 86.8. QwQ Base is 0.4 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 86.4 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 $3.68 per million input tokens, QwQ Base 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
Claude Sonnet 4.5 Mini Anthropic 32768 $11.43 76.5
Command R+ Cohere 32768 $3.96 76.3
MiniMax-Text Chat MiniMax 128000 $4.26 77.8
Phi-4 Chat Microsoft 65536 $3.66 74.7
QwQ Base Alibaba Cloud 65536 $3.68 74.1
Reka Core Max Reka AI 128000 $13.41 79.3
o3 Mini OpenAI 128000 $10.68 76.2

Other benchmarks for QwQ Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.5 263 56th
GPQA Diamond 69.9 268 55th
SWE-bench Verified 65.2 211 65th
HumanEval 77.0 308 49th
MATH-500 77.5 266 56th
AIME 2025 66.2 326 46th
LiveCodeBench 64.0 319 47th
IFEval 81.2 303 50th
TruthfulQA 79.8 190 68th
MMMU 70.0 304 49th
Arena Elo 1373.8 300 50th

FAQ

What score does QwQ Base get on HellaSwag?

QwQ Base scores 86.4 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does QwQ Base rank on HellaSwag?

It ranks #201 of 600 models, in the 67th percentile. The leader is GPT-5.2 Max at 96.1.

Is QwQ Base good at HellaSwag?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Base cost?

QwQ Base costs $3.68 per million input tokens and $15.98 per million output tokens.

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