Multimodal · Meta AI

Llama 3.1 8B on MMMU: score, rank and what it means

Llama 3.1 8B scores 59.4 on MMMU, placing it #434 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
59.4
0–100 scale
Rank
#434
of 600
Percentile
28th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
27.5
points

Score distribution

The chart shows the top 10 models on MMMU, with Llama 3.1 8B 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 8B sits at #434 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 27.5 points. The median model in this index scores 70.0, which puts Llama 3.1 8B below the midpoint.

Meta AI models average 66.5 on this benchmark. Llama 3.1 8B is 7.1 points below that provider line, so it is a weaker result than the average Meta AI model.

Among small open-weight models, the average is 52.4. Llama 3.1 8B is 7.0 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 59.4 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 $1.15 per million input tokens, Llama 3.1 8B 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
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9
Mistral Large 3 8B Mistral AI 16384 $1.62 61.6
GLM-4.5 7B Zhipu AI 8192 $1.32 60.2
Embed 4 Turbo Cohere 4096 $5.13 64.0
Llama 3.1 8B Meta AI 8192 $1.15 58.7
SmolLM3 Base Hugging Face 16384 $1.38 60.4
Auto Mini OpenRouter 4096 $4.24 61.6

Other benchmarks for Llama 3.1 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.5 445 26th
GPQA Diamond 51.2 508 15th
SWE-bench Verified 45.6 457 24th
HumanEval 64.3 449 25th
MATH-500 57.9 493 18th
AIME 2025 50.0 459 24th
LiveCodeBench 48.7 458 24th
IFEval 68.3 486 19th
TruthfulQA 62.3 498 17th
HellaSwag 72.4 488 19th
Arena Elo 1277.1 450 25th

FAQ

What score does Llama 3.1 8B get on MMMU?

Llama 3.1 8B scores 59.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Llama 3.1 8B rank on MMMU?

It ranks #434 of 600 models, in the 28th percentile. The leader is GPT-5.2 Max at 86.9.

Is Llama 3.1 8B 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 Llama 3.1 8B cost?

Llama 3.1 8B costs $1.15 per million input tokens and $4.48 per million output tokens.

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