Multimodal · Fireworks AI

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

Firefunction Pro scores 68.4 on MMMU, placing it #338 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
68.4
0–100 scale
Rank
#338
of 600
Percentile
44th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
18.5
points

Score distribution

The chart shows the top 10 models on MMMU, with Firefunction 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, Firefunction Pro sits at #338 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 18.5 points. The median model in this index scores 70.0, which puts Firefunction Pro below the midpoint.

Fireworks AI models average 65.3 on this benchmark. Firefunction Pro is 3.1 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 65.0. Firefunction Pro is 3.4 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 68.4 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 $9.05 per million input tokens, Firefunction 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
Fusion OpenRouter 16384 $8.41 71.1
Mistral Small 3 Base Mistral AI 16384 $3.19 72.7
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Seed-OSS Base ByteDance 16384 $3.14 72.2
Firefunction Pro Fireworks AI 16384 $9.05 72.9
Codestral Base Mistral AI 8192 $3.31 73.1
OLMo 2 Allen Institute for AI 65536 $2.99 71.0

Other benchmarks for Firefunction Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.6 315 48th
GPQA Diamond 66.1 342 43th
SWE-bench Verified 60.9 303 50th
HumanEval 76.5 319 47th
MATH-500 74.6 337 44th
AIME 2025 71.4 231 62th
LiveCodeBench 66.0 274 54th
IFEval 82.6 256 57th
TruthfulQA 74.8 333 45th
HellaSwag 85.0 242 60th
Arena Elo 1358.8 347 42th

FAQ

What score does Firefunction Pro get on MMMU?

Firefunction Pro scores 68.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Firefunction Pro rank on MMMU?

It ranks #338 of 600 models, in the 44th percentile. The leader is GPT-5.2 Max at 86.9.

Is Firefunction 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 Firefunction Pro cost?

Firefunction Pro costs $9.05 per million input tokens and $49.41 per million output tokens.

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