Multimodal · Together AI

Llama 3.1 Turbo 7B on MMMU: score, rank and what it means

Llama 3.1 Turbo 7B scores 56.7 on MMMU, placing it #476 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
56.7
0–100 scale
Rank
#476
of 600
Percentile
21th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
30.2
points

Score distribution

The chart shows the top 10 models on MMMU, with Llama 3.1 Turbo 7B 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 Turbo 7B sits at #476 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 30.2 points. The median model in this index scores 70.0, which puts Llama 3.1 Turbo 7B below the midpoint.

Together AI models average 62.9 on this benchmark. Llama 3.1 Turbo 7B is 6.2 points below that provider line, so it is a weaker result than the average Together AI model.

Among small open-weight models, the average is 52.4. Llama 3.1 Turbo 7B is 4.3 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 56.7 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 $0.98 per million input tokens, Llama 3.1 Turbo 7B 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
Zephyr Chat Hugging Face 4096 $1.49 61.3
GPT-NeoX Base EleutherAI 16384 $1.22 59.7
Gemma 3 7B Google DeepMind 32768 $0.90 55.9
Llama 3 Anyscale 8B Anyscale 32768 $0.97 57.3
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
Llama 3 Replicate 7B Replicate 32768 $0.91 56.0
Llama 3 Replicate 8B Replicate 32768 $1.00 57.0

Other benchmarks for Llama 3.1 Turbo 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.8 474 21th
GPQA Diamond 51.9 500 17th
SWE-bench Verified 43.8 481 20th
HumanEval 59.0 512 15th
MATH-500 55.8 510 15th
AIME 2025 44.6 501 17th
LiveCodeBench 44.2 506 16th
IFEval 65.9 520 13th
TruthfulQA 63.0 491 18th
HellaSwag 72.0 499 17th
Arena Elo 1245.4 497 17th

FAQ

What score does Llama 3.1 Turbo 7B get on MMMU?

Llama 3.1 Turbo 7B scores 56.7 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Llama 3.1 Turbo 7B rank on MMMU?

It ranks #476 of 600 models, in the 21st percentile. The leader is GPT-5.2 Max at 86.9.

Is Llama 3.1 Turbo 7B 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 Turbo 7B cost?

Llama 3.1 Turbo 7B costs $0.98 per million input tokens and $4.14 per million output tokens.

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