Multimodal · Google DeepMind

Gemma 3 Chat on MMMU: score, rank and what it means

Gemma 3 Chat scores 70.2 on MMMU, placing it #291 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
70.2
0–100 scale
Rank
#291
of 600
Percentile
52th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
16.7
points

Score distribution

The chart shows the top 10 models on MMMU, with Gemma 3 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, Gemma 3 Chat sits at #291 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 16.7 points. The median model in this index scores 70.0, which puts Gemma 3 Chat above the midpoint.

Google DeepMind models average 74.9 on this benchmark. Gemma 3 Chat is 4.7 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among multimodal models, the average is 74.3. Gemma 3 Chat is 4.1 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 70.2 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 $3.74 per million input tokens, Gemma 3 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
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
OLMo 2 Instruct Allen Institute for AI 32768 $3.03 71.7
DBRX Instruct Databricks 8192 $3.21 72.4
ERNIE 4.0 Baidu 32768 $11.37 76.7
Gemma 3 Chat Google DeepMind 65536 $3.74 74.5
Llama 3 Novita Novita AI 128000 $3.70 74.4
Mixtral Instruct Mistral AI 65536 $3.35 72.9

Other benchmarks for Gemma 3 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.4 200 67th
GPQA Diamond 67.7 316 47th
SWE-bench Verified 65.2 210 65th
HumanEval 79.2 258 57th
MATH-500 78.7 244 59th
AIME 2025 70.6 244 59th
LiveCodeBench 64.6 304 49th
IFEval 83.8 217 64th
TruthfulQA 76.5 292 51th
HellaSwag 84.1 276 54th
Arena Elo 1374.6 297 51th

FAQ

What score does Gemma 3 Chat get on MMMU?

Gemma 3 Chat scores 70.2 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Gemma 3 Chat rank on MMMU?

It ranks #291 of 600 models, in the 52nd percentile. The leader is GPT-5.2 Max at 86.9.

Is Gemma 3 Chat good at MMMU?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Gemma 3 Chat cost?

Gemma 3 Chat costs $3.74 per million input tokens and $15.14 per million output tokens.

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