Mathematics · Perplexity

Sonar Pro on MATH-500: score, rank and what it means

Sonar Pro scores 80.7 on MATH-500, placing it #196 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
80.7
0–100 scale
Rank
#196
of 600
Percentile
67th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
16.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Sonar Pro highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

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-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Sonar Pro sits at #196 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 16.0 points. The median model in this index scores 76.0, which puts Sonar Pro above the midpoint.

Perplexity models average 78.7 on this benchmark. Sonar Pro is 2.0 points above that provider line, so it is a stronger result than the average Perplexity model.

Among multimodal models, the average is 81.3. Sonar Pro is 0.6 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 80.7 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 $13.01 per million input tokens, Sonar Pro is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 4 Scout Meta AI 200000 $4.90 79.3
Llama 3.1 Cerebras Instruct Cerebras 65536 $4.11 76.1
Kimi K2 Base Moonshot AI 65536 $4.82 79.2
MiniMax-Text Instruct MiniMax 128000 $4.59 77.7
Sonar Pro Perplexity 128000 $13.01 79.1
Claude Haiku 4.5 Vision Anthropic 128000 $13.01 79.2
Llama 3 DeepInfra Chat DeepInfra 200000 $3.74 75.0

Other benchmarks for Sonar Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.7 224 63th
GPQA Diamond 77.1 105 83th
SWE-bench Verified 68.9 132 78th
HumanEval 82.6 170 72th
AIME 2025 74.7 162 73th
LiveCodeBench 75.0 96 84th
IFEval 87.4 125 79th
TruthfulQA 82.5 119 80th
HellaSwag 86.5 196 67th
MMMU 75.7 146 76th
Arena Elo 1411.3 181 70th

FAQ

What score does Sonar Pro get on MATH-500?

Sonar Pro scores 80.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Sonar Pro rank on MATH-500?

It ranks #196 of 600 models, in the 67th percentile. The leader is GPT-5.2 Max at 96.7.

Is Sonar Pro good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 Pro cost?

Sonar Pro costs $13.01 per million input tokens and $50.93 per million output tokens.

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