Multimodal · Groq

Llama 3.3 Groq Chat on MMMU: score, rank and what it means

Llama 3.3 Groq Chat scores 72.9 on MMMU, placing it #223 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
72.9
0–100 scale
Rank
#223
of 600
Percentile
63th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
14.0
points

Score distribution

The chart shows the top 10 models on MMMU, with Llama 3.3 Groq 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, Llama 3.3 Groq Chat sits at #223 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 14.0 points. The median model in this index scores 70.0, which puts Llama 3.3 Groq Chat above the midpoint.

Groq models average 62.8 on this benchmark. Llama 3.3 Groq Chat is 10.1 points above that provider line, so it is a stronger result than the average Groq model.

Among multimodal models, the average is 74.3. Llama 3.3 Groq 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 72.9 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 $4.06 per million input tokens, Llama 3.3 Groq Chat is above 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
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
Llama 3.3 Meta AI 128000 $4.56 78.2
Llama 4 Scout Instruct Meta AI 32768 $4.59 79.1
MiniMax-Text Instruct MiniMax 128000 $4.59 77.7
Llama 3.3 Groq Chat Groq 32768 $4.06 76.8
Mistral Small 3 Instruct Mistral AI 32768 $3.97 75.1
Seed-OSS Chat ByteDance 65536 $3.49 74.4

Other benchmarks for Llama 3.3 Groq Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.6 192 68th
GPQA Diamond 73.3 193 68th
SWE-bench Verified 66.9 171 72th
HumanEval 80.2 226 62th
MATH-500 78.2 252 58th
AIME 2025 74.2 172 71th
LiveCodeBench 71.3 163 73th
IFEval 83.6 226 62th
TruthfulQA 77.4 270 55th
HellaSwag 87.2 167 72th
Arena Elo 1412.7 178 70th

FAQ

What score does Llama 3.3 Groq Chat get on MMMU?

Llama 3.3 Groq Chat scores 72.9 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Llama 3.3 Groq Chat rank on MMMU?

It ranks #223 of 600 models, in the 63rd percentile. The leader is GPT-5.2 Max at 86.9.

Is Llama 3.3 Groq 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 Llama 3.3 Groq Chat cost?

Llama 3.3 Groq Chat costs $4.06 per million input tokens and $19.98 per million output tokens.

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