Mathematics · Baseten

Llama 3 Baseten Instruct on AIME 2025: score, rank and what it means

Llama 3 Baseten Instruct scores 74.7 on AIME 2025, placing it #159 of 600 models in the index. The benchmark average is 63.6 and the leader is Claude Opus 4.5 Pro at 91.4.

Score
74.7
0–100 scale
Rank
#159
of 600
Percentile
74th
within the index
Benchmark avg
63.6
all models
Leader
91.4
Claude Opus 4.5 Pro
Gap to leader
16.7
points

Score distribution

The chart shows the top 10 models on AIME 2025, with Llama 3 Baseten Instruct highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Pro 91.4
GPT-5.2 Pro 91.0
GPT-5.1 Pro 90.6
GPT-5.2 90.6
o4 Reasoning 90.3
o4 Pro 89.9
Claude Opus 4.5 89.8
Gemini 3 Pro Max 89.6
Claude Opus 4.5 Max 89.3
Claude Opus 4.5 Reasoning 88.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 GPT-5.2 OpenAI 2000000 $19.71 88.0
5 o4 Reasoning OpenAI 1000000 $19.69 87.5
6 o4 Pro OpenAI 1000000 $19.37 87.3
7 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
8 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On AIME 2025, Llama 3 Baseten Instruct sits at #159 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 16.7 points. The median model in this index scores 67.6, which puts Llama 3 Baseten Instruct above the midpoint.

Baseten models average 58.2 on this benchmark. Llama 3 Baseten Instruct is 16.5 points above that provider line, so it is a stronger result than the average Baseten model.

Among multimodal models, the average is 73.9. Llama 3 Baseten Instruct is 0.8 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 74.7 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 $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 AIME 2025. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command R+ Cohere 32768 $3.96 76.3
Sonar Max Perplexity 32768 $11.60 77.8
Sonar Pro Max Perplexity 128000 $14.01 81.1
Llama 3 Lambda Instruct Lambda 32768 $3.92 75.8
Llama 3 Baseten Instruct Baseten 200000 $3.91 76.2
Llama 3.3 Groq Instruct Groq 65536 $4.08 76.7
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0

Other benchmarks for Llama 3 Baseten Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.0 182 70th
GPQA Diamond 73.9 171 72th
SWE-bench Verified 62.8 257 57th
HumanEval 78.6 273 55th
MATH-500 77.4 269 55th
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 AIME 2025?

Llama 3 Baseten Instruct scores 74.7 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.

How does Llama 3 Baseten Instruct rank on AIME 2025?

It ranks #159 of 600 models, in the 74th percentile. The leader is Claude Opus 4.5 Pro at 91.4.

Is Llama 3 Baseten Instruct good at AIME 2025?

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 AIME 2025 score calculated?

AIME 2025 is a mathematics 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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