Coding · Perplexity

Sonar Max on SWE-bench Verified: score, rank and what it means

Sonar Max scores 63.0 on SWE-bench Verified, placing it #253 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
63.0
0–100 scale
Rank
#253
of 600
Percentile
58th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
18.7
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Sonar Max highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Sonar Max sits at #253 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 18.7 points. The median model in this index scores 61.0, which puts Sonar Max above the midpoint.

Perplexity models average 63.8 on this benchmark. Sonar Max is 0.8 points below that provider line, so it is a weaker result than the average Perplexity model.

Among multimodal models, the average is 66.4. Sonar Max is 3.4 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 63.0 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 $11.60 per million input tokens, Sonar Max is above the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Seed-OSS Instruct ByteDance 128000 $3.79 76.0
Llama 3 Novita Instruct Novita AI 32768 $3.94 75.6
GPT-5.1 Nano OpenAI 32768 $9.56 74.1
Llama 3 Anyscale Anyscale 65536 $3.94 74.7
Sonar Max Perplexity 32768 $11.60 77.8
Llama 3 Baseten Base Baseten 16384 $3.16 72.4
Llama 3 Baseten Chat Baseten 200000 $3.55 73.2

Other benchmarks for Sonar Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.3 141 77th
GPQA Diamond 73.7 180 70th
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
MMMU 75.4 156 74th
Arena Elo 1395.2 227 62th

FAQ

What score does Sonar Max get on SWE-bench Verified?

Sonar Max scores 63.0 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Sonar Max rank on SWE-bench Verified?

It ranks #253 of 600 models, in the 58th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Sonar Max good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified is a coding 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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