Coding · OpenRouter

Auto Turbo on LiveCodeBench: score, rank and what it means

Auto Turbo scores 60.2 on LiveCodeBench, placing it #366 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
60.2
0–100 scale
Rank
#366
of 600
Percentile
39th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
24.9
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Auto Turbo highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Auto Turbo sits at #366 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 24.9 points. The median model in this index scores 64.7, which puts Auto Turbo below the midpoint.

OpenRouter models average 58.5 on this benchmark. Auto Turbo is 1.7 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 58.3. Auto Turbo is 1.9 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 60.2 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 $7.96 per million input tokens, Auto Turbo is above the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Fusion Turbo OpenRouter 8192 $8.55 71.7
Llama 3 Novita Base Novita AI 8192 $3.06 70.3
Gemini 3 Flash Nano Google DeepMind 32768 $7.56 69.4
o3 Nano OpenAI 32768 $7.78 70.6
Auto Turbo OpenRouter 65536 $7.96 70.9
Command A Mini Cohere 8192 $8.12 71.0
Auto Max OpenRouter 8192 $8.41 71.2

Other benchmarks for Auto Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 305 49th
GPQA Diamond 69.1 291 52th
SWE-bench Verified 57.1 365 39th
HumanEval 75.7 332 45th
MATH-500 71.2 377 37th
AIME 2025 64.8 340 43th
IFEval 80.7 318 47th
TruthfulQA 71.7 383 36th
HellaSwag 83.9 283 53th
MMMU 70.0 301 50th
Arena Elo 1345.5 371 38th

FAQ

What score does Auto Turbo get on LiveCodeBench?

Auto Turbo scores 60.2 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Auto Turbo rank on LiveCodeBench?

It ranks #366 of 600 models, in the 39th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Auto Turbo good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench 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 Turbo cost?

Auto Turbo costs $7.96 per million input tokens and $33.26 per million output tokens.

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