Coding · Fireworks AI

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

Firesearch Pro scores 75.3 on HumanEval, placing it #338 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
75.3
0–100 scale
Rank
#338
of 600
Percentile
44th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
21.5
points

Score distribution

The chart shows the top 10 models on HumanEval, with Firesearch Pro 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 Pro sits at #338 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 21.5 points. The median model in this index scores 77.4, which puts Firesearch Pro below the midpoint.

Fireworks AI models average 71.5 on this benchmark. Firesearch Pro is 3.8 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 71.5. Firesearch Pro is 3.8 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 75.3 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 $7.67 per million input tokens, Firesearch Pro is above 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
Claude Opus 4.5 Nano Anthropic 32768 $9.38 73.3
Mixtral Groq Chat Groq 8192 $3.09 72.0
Doubao 1.5 Pro Mini ByteDance 32768 $8.30 72.3
ERNIE 4.0 Mini Baidu 32768 $7.11 68.8
Firesearch Pro Fireworks AI 32768 $7.67 70.4
Llama 3 Lambda Base Lambda 8192 $3.19 72.9
Auto OpenRouter 32768 $7.53 70.2

Other benchmarks for Firesearch Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.6 370 38th
GPQA Diamond 68.4 305 49th
SWE-bench Verified 59.8 330 45th
MATH-500 70.2 384 36th
AIME 2025 61.0 382 36th
LiveCodeBench 63.9 320 47th
IFEval 80.1 331 45th
TruthfulQA 72.8 371 38th
HellaSwag 81.2 362 40th
MMMU 68.7 330 45th
Arena Elo 1362.0 340 43th

FAQ

What score does Firesearch Pro get on HumanEval?

Firesearch Pro scores 75.3 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Firesearch Pro rank on HumanEval?

It ranks #338 of 600 models, in the 44th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Firesearch Pro 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 Pro cost?

Firesearch Pro costs $7.67 per million input tokens and $32.83 per million output tokens.

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