Mathematics · Fireworks AI

Firesearch Nano on AIME 2025: score, rank and what it means

Firesearch Nano scores 45.7 on AIME 2025, placing it #492 of 600 models in the index. The benchmark average is 63.6 and the leader is Claude Opus 4.5 Pro at 91.4.

Score
45.7
0–100 scale
Rank
#492
of 600
Percentile
18th
within the index
Benchmark avg
63.6
all models
Leader
91.4
Claude Opus 4.5 Pro
Gap to leader
45.7
points

Score distribution

The chart shows the top 10 models on AIME 2025, with Firesearch Nano highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Pro 91.4
GPT-5.2 Pro 91.0
GPT-5.1 Pro 90.6
GPT-5.2 90.6
o4 Reasoning 90.3
o4 Pro 89.9
Claude Opus 4.5 89.8
Gemini 3 Pro Max 89.6
Claude Opus 4.5 Max 89.3
Claude Opus 4.5 Reasoning 88.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 GPT-5.2 OpenAI 2000000 $19.71 88.0
5 o4 Reasoning OpenAI 1000000 $19.69 87.5
6 o4 Pro OpenAI 1000000 $19.37 87.3
7 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
8 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
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 AIME 2025, Firesearch Nano sits at #492 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 45.7 points. The median model in this index scores 67.6, which puts Firesearch Nano below the midpoint.

Fireworks AI models average 60.5 on this benchmark. Firesearch Nano is 14.8 points below that provider line, so it is a weaker result than the average Fireworks AI model.

Among mid-range models, the average is 60.1. Firesearch Nano is 14.4 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 45.7 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 $2.49 per million input tokens, Firesearch Nano is below the median input price of $4.00 across the 600 models scored on AIME 2025. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Anyscale 7B Anyscale 4096 $0.98 56.2
Magistral 7B Mistral AI 32768 $1.22 58.9
Yi-Large 7B 01.AI 4096 $0.83 55.0
DBRX 8B Databricks 4096 $0.82 54.1
Firesearch Nano Fireworks AI 8192 $2.49 55.6
Llama 3 Replicate 7B Replicate 32768 $0.91 56.0
DeepSeek-V3.2 1.5B DeepSeek 4096 $1.02 56.9

Other benchmarks for Firesearch Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.0 488 19th
GPQA Diamond 52.6 493 18th
SWE-bench Verified 40.0 521 13th
HumanEval 58.9 513 15th
MATH-500 52.9 533 11th
LiveCodeBench 41.5 529 12th
IFEval 66.5 509 15th
TruthfulQA 62.6 495 18th
HellaSwag 73.2 475 21th
MMMU 54.8 500 17th
Arena Elo 1229.9 526 12th

FAQ

What score does Firesearch Nano get on AIME 2025?

Firesearch Nano scores 45.7 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.

How does Firesearch Nano rank on AIME 2025?

It ranks #492 of 600 models, in the 18th percentile. The leader is Claude Opus 4.5 Pro at 91.4.

Is Firesearch Nano good at AIME 2025?

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 AIME 2025 score calculated?

AIME 2025 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 Firesearch Nano cost?

Firesearch Nano costs $2.49 per million input tokens and $11.16 per million output tokens.

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