Knowledge · OpenRouter

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

Fusion Reasoning scores 73.3 on MMLU-Pro, placing it #365 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
73.3
0–100 scale
Rank
#365
of 600
Percentile
39th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
18.3
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Fusion Reasoning 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 Reasoning sits at #365 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 18.3 points. The median model in this index scores 76.1, which puts Fusion Reasoning below the midpoint.

OpenRouter models average 72.7 on this benchmark. Fusion Reasoning is 0.6 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 Reasoning is 1.8 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 73.3 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 $8.59 per million input tokens, Fusion Reasoning 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
Arctic Chat Snowflake 16384 $2.70 69.8
Auto OpenRouter 32768 $7.53 70.2
Llama 3 Baseten Base Baseten 16384 $3.16 72.4
Mixtral Groq Chat Groq 8192 $3.09 72.0
Fusion Reasoning OpenRouter 65536 $8.59 72.2
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1
Hunyuan-Turbo Mini Tencent 8192 $6.59 68.3

Other benchmarks for Fusion Reasoning

BenchmarkScoreRankPercentileRelative
GPQA Diamond 67.4 323 46th
SWE-bench Verified 61.7 288 52th
HumanEval 78.2 285 53th
MATH-500 73.1 356 41th
AIME 2025 63.3 364 39th
LiveCodeBench 66.6 259 57th
IFEval 82.0 278 54th
TruthfulQA 73.8 358 40th
HellaSwag 84.1 274 54th
MMMU 71.0 272 55th
Arena Elo 1357.6 348 42th

FAQ

What score does Fusion Reasoning get on MMLU-Pro?

Fusion Reasoning scores 73.3 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Fusion Reasoning rank on MMLU-Pro?

It ranks #365 of 600 models, in the 39th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Fusion Reasoning 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 Reasoning cost?

Fusion Reasoning costs $8.59 per million input tokens and $32.34 per million output tokens.

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