Multimodal · Microsoft

Phi-3.5 Chat on MMMU: score, rank and what it means

Phi-3.5 Chat scores 63.7 on MMMU, placing it #393 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
63.7
0–100 scale
Rank
#393
of 600
Percentile
35th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
23.2
points

Score distribution

The chart shows the top 10 models on MMMU, with Phi-3.5 Chat 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, Phi-3.5 Chat sits at #393 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 23.2 points. The median model in this index scores 70.0, which puts Phi-3.5 Chat below the midpoint.

Microsoft models average 59.7 on this benchmark. Phi-3.5 Chat is 4.0 points above that provider line, so it is a stronger result than the average Microsoft model.

Among open-weight models, the average is 65.1. Phi-3.5 Chat is 1.4 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 63.7 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 $2.64 per million input tokens, Phi-3.5 Chat is below 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
Firesearch Turbo Fireworks AI 16384 $7.58 69.3
Mixtral Groq Base Groq 32768 $2.66 68.4
Arctic Snowflake 8192 $2.72 68.8
Nova Pro Nano Amazon 8192 $5.44 65.4
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Grok 3 Nano xAI 8192 $7.12 67.8
Firefunction Mini Fireworks AI 32768 $4.63 63.2

Other benchmarks for Phi-3.5 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.4 345 43th
GPQA Diamond 64.9 362 40th
SWE-bench Verified 56.6 372 38th
HumanEval 71.0 389 35th
MATH-500 69.0 388 35th
AIME 2025 64.6 346 42th
LiveCodeBench 62.6 340 43th
IFEval 79.2 352 41th
TruthfulQA 72.4 377 37th
HellaSwag 80.9 373 38th
Arena Elo 1338.0 380 37th

FAQ

What score does Phi-3.5 Chat get on MMMU?

Phi-3.5 Chat scores 63.7 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Phi-3.5 Chat rank on MMMU?

It ranks #393 of 600 models, in the 35th percentile. The leader is GPT-5.2 Max at 86.9.

Is Phi-3.5 Chat 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 Phi-3.5 Chat cost?

Phi-3.5 Chat costs $2.64 per million input tokens and $12.13 per million output tokens.

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