Multimodal · Microsoft

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

Phi-3.5 Instruct scores 65.3 on MMMU, placing it #379 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
65.3
0–100 scale
Rank
#379
of 600
Percentile
37th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
21.6
points

Score distribution

The chart shows the top 10 models on MMMU, with Phi-3.5 Instruct 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 Instruct sits at #379 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 21.6 points. The median model in this index scores 70.0, which puts Phi-3.5 Instruct below the midpoint.

Microsoft models average 59.7 on this benchmark. Phi-3.5 Instruct is 5.6 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 Instruct is 0.2 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 65.3 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 $2.67 per million input tokens, Phi-3.5 Instruct 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
Molmo Instruct Allen Institute for AI 32768 $2.53 68.3
Claude 3.7 Sonnet Nano Anthropic 65536 $6.93 68.9
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
Doubao 1.5 Pro Nano ByteDance 16384 $5.78 66.6
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1
Command A Nano Cohere 8192 $5.90 66.3
Arctic Instruct Snowflake 65536 $2.83 70.6

Other benchmarks for Phi-3.5 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.9 338 44th
GPQA Diamond 65.5 352 41th
SWE-bench Verified 56.1 376 37th
HumanEval 72.1 378 37th
MATH-500 74.6 338 44th
AIME 2025 66.6 323 46th
LiveCodeBench 59.6 373 38th
IFEval 79.2 353 41th
TruthfulQA 75.3 326 46th
HellaSwag 82.2 343 43th
Arena Elo 1346.8 369 39th

FAQ

What score does Phi-3.5 Instruct get on MMMU?

Phi-3.5 Instruct scores 65.3 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Phi-3.5 Instruct rank on MMMU?

It ranks #379 of 600 models, in the 37th percentile. The leader is GPT-5.2 Max at 86.9.

Is Phi-3.5 Instruct 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 Instruct cost?

Phi-3.5 Instruct costs $2.67 per million input tokens and $14.62 per million output tokens.

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