Multimodal · Together AI

Llama 3.1 Turbo 1.5B on MMMU: score, rank and what it means

Llama 3.1 Turbo 1.5B scores 50.0 on MMMU, placing it #554 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
50.0
0–100 scale
Rank
#554
of 600
Percentile
8th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
36.9
points

Score distribution

The chart shows the top 10 models on MMMU, with Llama 3.1 Turbo 1.5B 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 1.5B sits at #554 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 36.9 points. The median model in this index scores 70.0, which puts Llama 3.1 Turbo 1.5B below the midpoint.

Together AI models average 62.9 on this benchmark. Llama 3.1 Turbo 1.5B is 12.9 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 1.5B is 2.4 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 50.0 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 $0.46 per million input tokens, Llama 3.1 Turbo 1.5B 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
OLMo 2 8B Allen Institute for AI 4096 $0.64 52.5
Mixtral Groq 7B Groq 4096 $0.70 53.4
Molmo 7B Allen Institute for AI 32768 $0.42 49.3
OLMo 2 7B Allen Institute for AI 16384 $0.56 51.7
Llama 3.1 Turbo 1.5B Together AI 16384 $0.46 49.8
Llama 4 Scout 1.5B Meta AI 8192 $0.66 53.0
MiniMax-Text 1.5B MiniMax 32768 $0.58 51.5

Other benchmarks for Llama 3.1 Turbo 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 57.8 551 8th
GPQA Diamond 43.7 572 5th
SWE-bench Verified 34.7 560 7th
HumanEval 50.4 571 5th
MATH-500 49.9 558 7th
AIME 2025 33.2 576 4th
LiveCodeBench 38.1 549 9th
IFEval 63.7 541 10th
TruthfulQA 56.6 557 7th
HellaSwag 69.4 543 10th
Arena Elo 1184.1 570 5th

FAQ

What score does Llama 3.1 Turbo 1.5B get on MMMU?

Llama 3.1 Turbo 1.5B scores 50.0 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Llama 3.1 Turbo 1.5B rank on MMMU?

It ranks #554 of 600 models, in the 8th percentile. The leader is GPT-5.2 Max at 86.9.

Is Llama 3.1 Turbo 1.5B 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 1.5B cost?

Llama 3.1 Turbo 1.5B costs $0.46 per million input tokens and $2.24 per million output tokens.

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