Commonsense · Perplexity

Sonar Max on HellaSwag: score, rank and what it means

Sonar Max scores 85.3 on HellaSwag, placing it #232 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
85.3
0–100 scale
Rank
#232
of 600
Percentile
61th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
10.8
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Sonar Max 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, Sonar Max sits at #232 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 10.8 points. The median model in this index scores 83.6, which puts Sonar Max above the midpoint.

Perplexity models average 84.7 on this benchmark. Sonar Max is 0.6 points above that provider line, so it is a stronger result than the average Perplexity model.

Among multimodal models, the average is 86.8. Sonar Max is 1.5 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 85.3 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 $11.60 per million input tokens, Sonar Max 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
Qwen3-Coder Base Alibaba Cloud 200000 $3.99 76.6
Sonar Pro Perplexity 65536 $11.25 77.1
Qwen3 Base Alibaba Cloud 65536 $4.33 77.4
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
Sonar Max Perplexity 32768 $11.60 77.8
Llama 3 Anyscale Instruct Anyscale 200000 $3.91 75.7
Llama 3 Lambda Base Lambda 8192 $3.19 72.9

Other benchmarks for Sonar Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.3 141 77th
GPQA Diamond 73.7 180 70th
SWE-bench Verified 63.0 253 58th
HumanEval 82.1 186 69th
MATH-500 83.3 143 76th
AIME 2025 74.9 156 74th
LiveCodeBench 72.8 133 78th
IFEval 85.2 188 69th
TruthfulQA 78.9 224 63th
MMMU 75.4 156 74th
Arena Elo 1395.2 227 62th

FAQ

What score does Sonar Max get on HellaSwag?

Sonar Max scores 85.3 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Sonar Max rank on HellaSwag?

It ranks #232 of 600 models, in the 61st percentile. The leader is GPT-5.2 Max at 96.1.

Is Sonar Max 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 Sonar Max cost?

Sonar Max costs $11.60 per million input tokens and $42.81 per million output tokens.

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