Coding · Fireworks AI

Firesearch on HumanEval: score, rank and what it means

Firesearch scores 73.6 on HumanEval, placing it #365 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
73.6
0–100 scale
Rank
#365
of 600
Percentile
39th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
23.2
points

Score distribution

The chart shows the top 10 models on HumanEval, with Firesearch 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 sits at #365 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 23.2 points. The median model in this index scores 77.4, which puts Firesearch below the midpoint.

Fireworks AI models average 71.5 on this benchmark. Firesearch is 2.1 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 is 2.1 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 73.6 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 $7.03 per million input tokens, Firesearch 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
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
Hunyuan-Turbo Mini Tencent 8192 $6.59 68.3
Mixtral Base Mistral AI 65536 $2.95 71.1
DBRX Chat Databricks 65536 $3.07 71.7
Firesearch Fireworks AI 32768 $7.03 68.5
Firesearch Turbo Fireworks AI 16384 $7.58 69.3
Firefunction Turbo Fireworks AI 32768 $8.44 70.7

Other benchmarks for Firesearch

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.6 384 36th
GPQA Diamond 65.0 359 40th
SWE-bench Verified 55.6 380 37th
MATH-500 68.4 394 34th
AIME 2025 59.1 393 35th
LiveCodeBench 57.1 393 35th
IFEval 78.1 367 39th
TruthfulQA 75.1 328 45th
HellaSwag 82.4 338 44th
MMMU 67.4 353 41th
Arena Elo 1353.2 358 40th

FAQ

What score does Firesearch get on HumanEval?

Firesearch scores 73.6 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Firesearch rank on HumanEval?

It ranks #365 of 600 models, in the 39th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Firesearch 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 cost?

Firesearch costs $7.03 per million input tokens and $29.81 per million output tokens.

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