Coding · Fireworks AI

Firesearch Nano on HumanEval: score, rank and what it means

Firesearch Nano scores 58.9 on HumanEval, placing it #513 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
58.9
0–100 scale
Rank
#513
of 600
Percentile
15th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
37.9
points

Score distribution

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

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Firesearch Nano sits at #513 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 37.9 points. The median model in this index scores 77.4, which puts Firesearch Nano below the midpoint.

Fireworks AI models average 71.5 on this benchmark. Firesearch Nano is 12.6 points below that provider line, so it is a weaker result than the average Fireworks AI model.

Among mid-range models, the average is 71.5. Firesearch Nano is 12.6 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 58.9 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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Pythia Base EleutherAI 16384 $0.99 55.9
Llama 3 Novita 8B Novita AI 16384 $0.99 55.5
Llama 3 Anyscale 8B Anyscale 32768 $0.97 57.3
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
Firesearch Nano Fireworks AI 8192 $2.49 55.6
Llama 3 Modal 7B Modal 4096 $0.88 55.2
Command R+ 7B Cohere 8192 $0.95 56.2

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
MATH-500 52.9 533 11th
AIME 2025 45.7 492 18th
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 HumanEval?

Firesearch Nano scores 58.9 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Firesearch Nano rank on HumanEval?

It ranks #513 of 600 models, in the 15th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Firesearch Nano good at HumanEval?

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 HumanEval score calculated?

HumanEval 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 Firesearch Nano cost?

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

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