Multimodal · Perplexity

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

Sonar Max scores 75.4 on MMMU, placing it #156 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
75.4
0–100 scale
Rank
#156
of 600
Percentile
74th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
11.5
points

Score distribution

The chart shows the top 10 models on MMMU, with Sonar Max highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Sonar Max sits at #156 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 11.5 points. The median model in this index scores 70.0, which puts Sonar Max above the midpoint.

Perplexity models average 71.2 on this benchmark. Sonar Max is 4.2 points above that provider line, so it is a stronger result than the average Perplexity model.

Among multimodal models, the average is 74.3. Sonar Max is 1.1 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 75.4 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 $11.60 per million input tokens, Sonar Max is above the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command A Turbo Cohere 32768 $13.53 79.8
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
GLM-4.6 Zhipu AI 128000 $5.10 80.2
Llama 4 Maverick Chat Meta AI 128000 $5.09 79.7
Sonar Max Perplexity 32768 $11.60 77.8
Claude Haiku 4.5 Pro Anthropic 1000000 $15.07 80.8
Llama 3.3 Groq Groq 32768 $3.98 76.8

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
HellaSwag 85.3 232 61th
Arena Elo 1395.2 227 62th

FAQ

What score does Sonar Max get on MMMU?

Sonar Max scores 75.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Sonar Max rank on MMMU?

It ranks #156 of 600 models, in the 74th percentile. The leader is GPT-5.2 Max at 86.9.

Is Sonar Max good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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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