Reasoning · OpenRouter

Auto Nano on GPQA Diamond: score, rank and what it means

Auto Nano scores 50.2 on GPQA Diamond, placing it #520 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
50.2
0–100 scale
Rank
#520
of 600
Percentile
13th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
36.8
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Auto Nano highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Auto Nano sits at #520 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 36.8 points. The median model in this index scores 68.8, which puts Auto Nano below the midpoint.

OpenRouter models average 63.7 on this benchmark. Auto Nano is 13.5 points below that provider line, so it is a weaker result than the average OpenRouter model.

Among mid-range models, the average is 62.9. Auto Nano is 12.7 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 50.2 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 $2.83 per million input tokens, Auto Nano is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Hyperbolic 8B Hyperbolic 16384 $0.92 56.0
Yi-Lightning 7B 01.AI 32768 $1.00 55.9
OLMo 2 8B Allen Institute for AI 4096 $0.64 52.5
Gemma 3 8B Google DeepMind 16384 $0.96 56.5
Auto Nano OpenRouter 4096 $2.83 57.1
Llama 4 Scout 1.5B Meta AI 8192 $0.66 53.0
Llama 3 Hyperbolic 7B Hyperbolic 4096 $0.94 55.6

Other benchmarks for Auto Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.0 453 25th
SWE-bench Verified 44.2 475 21th
HumanEval 62.7 461 23th
MATH-500 60.0 464 23th
AIME 2025 44.2 505 16th
LiveCodeBench 46.5 483 20th
IFEval 66.5 508 15th
TruthfulQA 61.7 509 15th
HellaSwag 72.2 490 18th
MMMU 55.2 494 18th
Arena Elo 1256.0 481 20th

FAQ

What score does Auto Nano get on GPQA Diamond?

Auto Nano scores 50.2 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Auto Nano rank on GPQA Diamond?

It ranks #520 of 600 models, in the 13th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Auto Nano good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Nano cost?

Auto Nano costs $2.83 per million input tokens and $14.41 per million output tokens.

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