Multimodal · Cerebras

Llama 3.1 Cerebras on MMMU: score, rank and what it means

Llama 3.1 Cerebras scores 70.1 on MMMU, placing it #298 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
70.1
0–100 scale
Rank
#298
of 600
Percentile
50th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
16.8
points

Score distribution

The chart shows the top 10 models on MMMU, with Llama 3.1 Cerebras 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 3.1 Cerebras sits at #298 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 16.8 points. The median model in this index scores 70.0, which puts Llama 3.1 Cerebras above the midpoint.

Cerebras models average 62.9 on this benchmark. Llama 3.1 Cerebras is 7.2 points above that provider line, so it is a stronger result than the average Cerebras model.

Among multimodal models, the average is 74.3. Llama 3.1 Cerebras is 4.2 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 70.1 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 $4.01 per million input tokens, Llama 3.1 Cerebras 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
Phi-4 Chat Microsoft 65536 $3.66 74.7
o3 Nano OpenAI 32768 $7.78 70.6
o4 Nano OpenAI 65536 $8.61 72.0
Claude Sonnet 4.5 Nano Anthropic 8192 $8.93 72.0
Llama 3.1 Cerebras Cerebras 128000 $4.01 76.0
MiniMax-Text Base MiniMax 128000 $3.66 74.9
Sonar Perplexity 200000 $10.57 76.0

Other benchmarks for Llama 3.1 Cerebras

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.4 295 51th
GPQA Diamond 74.4 156 74th
SWE-bench Verified 64.9 214 64th
HumanEval 81.3 204 66th
MATH-500 82.4 155 74th
AIME 2025 69.8 260 57th
LiveCodeBench 66.1 273 55th
IFEval 84.6 199 67th
TruthfulQA 80.6 166 72th
HellaSwag 85.1 239 60th
Arena Elo 1411.3 179 70th

FAQ

What score does Llama 3.1 Cerebras get on MMMU?

Llama 3.1 Cerebras scores 70.1 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Llama 3.1 Cerebras rank on MMMU?

It ranks #298 of 600 models, in the 50th percentile. The leader is GPT-5.2 Max at 86.9.

Is Llama 3.1 Cerebras 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 3.1 Cerebras cost?

Llama 3.1 Cerebras costs $4.01 per million input tokens and $15.13 per million output tokens.

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