Coding · OpenRouter

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

Auto scores 58.1 on SWE-bench Verified, placing it #355 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
58.1
0–100 scale
Rank
#355
of 600
Percentile
41th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
23.6
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Auto 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, Auto sits at #355 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 23.6 points. The median model in this index scores 61.0, which puts Auto below the midpoint.

OpenRouter models average 55.2 on this benchmark. Auto is 2.9 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 54.9. Auto is 3.2 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 58.1 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 $7.53 per million input tokens, Auto 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
Firefunction Reasoning Fireworks AI 8192 $9.08 72.5
Llama 3 DeepInfra Base DeepInfra 16384 $2.95 71.8
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
Auto OpenRouter 32768 $7.53 70.2
Mixtral Turbo Base Together AI 32768 $2.53 69.7
Molmo Allen Institute for AI 32768 $2.49 68.5

Other benchmarks for Auto

BenchmarkScoreRankPercentileRelative
MMLU-Pro 73.6 362 40th
GPQA Diamond 63.9 378 37th
HumanEval 75.2 340 43th
MATH-500 74.1 343 43th
AIME 2025 67.0 313 48th
LiveCodeBench 59.0 378 37th
IFEval 77.3 375 38th
TruthfulQA 73.8 357 41th
HellaSwag 81.1 364 39th
MMMU 69.6 314 48th
Arena Elo 1341.2 378 37th

FAQ

What score does Auto get on SWE-bench Verified?

Auto scores 58.1 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Auto rank on SWE-bench Verified?

It ranks #355 of 600 models, in the 41st percentile. The leader is GPT-5.2 Pro at 81.7.

Is Auto good at SWE-bench Verified?

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 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 Auto cost?

Auto costs $7.53 per million input tokens and $29.19 per million output tokens.

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