Knowledge · Fireworks AI

Firesearch Mini on MMLU-Pro: score, rank and what it means

Firesearch Mini scores 67.5 on MMLU-Pro, placing it #424 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
67.5
0–100 scale
Rank
#424
of 600
Percentile
29th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
24.1
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Firesearch Mini highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Firesearch Mini sits at #424 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 24.1 points. The median model in this index scores 76.1, which puts Firesearch Mini below the midpoint.

Fireworks AI models average 71.6 on this benchmark. Firesearch Mini is 4.1 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 Mini is 4.0 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 67.5 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 $3.94 per million input tokens, Firesearch Mini is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
GPT-NeoX Instruct EleutherAI 16384 $1.52 62.6
StableLM 2 Base Stability AI 8192 $1.49 61.9
GPT-NeoX EleutherAI 16384 $1.57 61.7
Qwen3-Coder 8B Alibaba Cloud 32768 $1.43 61.3
Firesearch Mini Fireworks AI 32768 $3.94 61.5
Llama 4 Scout 8B Meta AI 8192 $1.46 61.2
Nova Pro Nano Amazon 8192 $5.44 65.4

Other benchmarks for Firesearch Mini

BenchmarkScoreRankPercentileRelative
GPQA Diamond 55.7 452 25th
SWE-bench Verified 48.8 432 28th
HumanEval 65.5 435 28th
MATH-500 59.6 471 22th
AIME 2025 50.8 453 25th
LiveCodeBench 50.9 440 27th
IFEval 72.8 420 30th
TruthfulQA 66.5 436 27th
HellaSwag 77.2 412 31th
MMMU 61.1 419 30th
Arena Elo 1280.3 445 26th

FAQ

What score does Firesearch Mini get on MMLU-Pro?

Firesearch Mini scores 67.5 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Firesearch Mini rank on MMLU-Pro?

It ranks #424 of 600 models, in the 29th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Firesearch Mini good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Mini cost?

Firesearch Mini costs $3.94 per million input tokens and $16.76 per million output tokens.

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