Mathematics · Perplexity

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

Sonar Pro Nano scores 69.0 on MATH-500, placing it #389 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
69.0
0–100 scale
Rank
#389
of 600
Percentile
35th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
27.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with Sonar Pro Nano 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 Nano sits at #389 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 27.7 points. The median model in this index scores 76.0, which puts Sonar Pro Nano below the midpoint.

Perplexity models average 78.7 on this benchmark. Sonar Pro Nano is 9.7 points below that provider line, so it is a weaker result than the average Perplexity model.

Among mid-range models, the average is 70.0. Sonar Pro Nano is 1.0 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 69.0 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 $5.50 per million input tokens, Sonar Pro Nano 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
Reka Core Nano Reka AI 16384 $5.45 65.1
Molmo Base Allen Institute for AI 4096 $2.02 65.0
Hunyuan-Turbo Mini Tencent 8192 $6.59 68.3
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Sonar Pro Nano Perplexity 32768 $5.50 66.1
Command A Nano Cohere 8192 $5.90 66.3
Embed 4 Turbo Cohere 4096 $5.13 64.0

Other benchmarks for Sonar Pro Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 68.6 410 32th
GPQA Diamond 62.5 387 36th
SWE-bench Verified 55.4 381 37th
HumanEval 69.6 402 33th
AIME 2025 58.8 395 34th
LiveCodeBench 58.2 388 35th
IFEval 73.1 416 31th
TruthfulQA 70.6 395 34th
HellaSwag 79.7 385 36th
MMMU 61.2 418 30th
Arena Elo 1328.5 390 35th

FAQ

What score does Sonar Pro Nano get on MATH-500?

Sonar Pro Nano scores 69.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Sonar Pro Nano rank on MATH-500?

It ranks #389 of 600 models, in the 35th percentile. The leader is GPT-5.2 Max at 96.7.

Is Sonar Pro Nano good at MATH-500?

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 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 Nano cost?

Sonar Pro Nano costs $5.50 per million input tokens and $22.25 per million output tokens.

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