Knowledge · Baseten

Llama 3 Baseten Instruct on MMLU-Pro: score, rank and what it means

Llama 3 Baseten Instruct scores 80.0 on MMLU-Pro, placing it #182 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
80.0
0–100 scale
Rank
#182
of 600
Percentile
70th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
11.6
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Llama 3 Baseten Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Llama 3 Baseten Instruct sits at #182 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 11.6 points. The median model in this index scores 76.1, which puts Llama 3 Baseten Instruct above the midpoint.

Baseten models average 69.8 on this benchmark. Llama 3 Baseten Instruct is 10.2 points above that provider line, so it is a stronger result than the average Baseten model.

Among multimodal models, the average is 80.0. Llama 3 Baseten Instruct is 0.0 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 80.0 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 $3.91 per million input tokens, Llama 3 Baseten Instruct is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command A Reasoning Cohere 400000 $13.74 80.2
Doubao 1.5 Pro Pro ByteDance 128000 $14.10 80.2
Codestral Chat Mistral AI 32768 $3.89 75.8
Nova Pro Amazon 32768 $12.75 79.4
Llama 3 Baseten Instruct Baseten 200000 $3.91 76.2
Llama 4 Scout Instruct Meta AI 32768 $4.59 79.1
MiniMax-M2 Base MiniMax 65536 $4.20 76.4

Other benchmarks for Llama 3 Baseten Instruct

BenchmarkScoreRankPercentileRelative
GPQA Diamond 73.9 171 72th
SWE-bench Verified 62.8 257 57th
HumanEval 78.6 273 55th
MATH-500 77.4 269 55th
AIME 2025 74.7 159 74th
LiveCodeBench 70.1 189 69th
IFEval 83.1 241 60th
TruthfulQA 79.3 205 66th
HellaSwag 86.8 184 69th
MMMU 72.0 244 59th
Arena Elo 1397.8 214 64th

FAQ

What score does Llama 3 Baseten Instruct get on MMLU-Pro?

Llama 3 Baseten Instruct scores 80.0 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Llama 3 Baseten Instruct rank on MMLU-Pro?

It ranks #182 of 600 models, in the 70th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Llama 3 Baseten Instruct good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Baseten Instruct cost?

Llama 3 Baseten Instruct costs $3.91 per million input tokens and $20.18 per million output tokens.

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