Multimodal · Fireworks AI

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

Firesearch Pro scores 68.7 on MMMU, placing it #330 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
68.7
0–100 scale
Rank
#330
of 600
Percentile
45th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
18.2
points

Score distribution

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

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Firesearch Pro sits at #330 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 18.2 points. The median model in this index scores 70.0, which puts Firesearch Pro below the midpoint.

Fireworks AI models average 65.3 on this benchmark. Firesearch Pro is 3.4 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 65.0. Firesearch Pro is 3.7 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 68.7 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 $7.67 per million input tokens, Firesearch Pro is above the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
OLMo 2 Chat Allen Institute for AI 16384 $2.94 70.6
Llama 3 Modal Base Modal 16384 $3.21 72.2
Phi-3.5 Microsoft 16384 $2.81 70.9
Doubao 1.5 Pro Mini ByteDance 32768 $8.30 72.3
Firesearch Pro Fireworks AI 32768 $7.67 70.4
Claude 3.7 Sonnet Mini Anthropic 32768 $9.74 73.0
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1

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
HumanEval 75.3 338 44th
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
Arena Elo 1362.0 340 43th

FAQ

What score does Firesearch Pro get on MMMU?

Firesearch Pro scores 68.7 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Firesearch Pro rank on MMMU?

It ranks #330 of 600 models, in the 45th percentile. The leader is GPT-5.2 Max at 86.9.

Is Firesearch Pro good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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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