Knowledge · OpenRouter

Fusion Max on MMLU-Pro: score, rank and what it means

Fusion Max scores 75.1 on MMLU-Pro, placing it #329 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
75.1
0–100 scale
Rank
#329
of 600
Percentile
45th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
16.5
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Fusion Max 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, Fusion Max sits at #329 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 16.5 points. The median model in this index scores 76.1, which puts Fusion Max below the midpoint.

OpenRouter models average 72.7 on this benchmark. Fusion Max is 2.4 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 71.5. Fusion Max is 3.6 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 75.1 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 $9.14 per million input tokens, Fusion Max is above 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
o3 Nano OpenAI 32768 $7.78 70.6
DBRX Chat Databricks 65536 $3.07 71.7
Gemma 3 Base Google DeepMind 65536 $3.09 71.1
Llama 3.1 Base Meta AI 32768 $3.39 72.2
Fusion Max OpenRouter 65536 $9.14 72.5
Gemma 3 Google DeepMind 65536 $3.68 73.6
Mixtral Groq Groq 16384 $3.37 73.1

Other benchmarks for Fusion Max

BenchmarkScoreRankPercentileRelative
GPQA Diamond 71.5 229 62th
SWE-bench Verified 59.1 340 43th
HumanEval 79.1 262 56th
MATH-500 74.1 344 43th
AIME 2025 65.1 337 44th
LiveCodeBench 63.3 334 44th
IFEval 81.4 288 52th
TruthfulQA 78.6 231 62th
HellaSwag 82.6 331 45th
MMMU 67.7 348 42th
Arena Elo 1359.7 345 43th

FAQ

What score does Fusion Max get on MMLU-Pro?

Fusion Max scores 75.1 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Fusion Max rank on MMLU-Pro?

It ranks #329 of 600 models, in the 45th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Fusion Max 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 Fusion Max cost?

Fusion Max costs $9.14 per million input tokens and $43.52 per million output tokens.

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