Mathematics · Meta AI

Llama 3.1 Instruct on AIME 2025: score, rank and what it means

Llama 3.1 Instruct scores 72.0 on AIME 2025, placing it #220 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
72.0
0–100 scale
Rank
#220
of 600
Percentile
63th
within the index
Benchmark avg
63.6
all models
Leader
91.4
Claude Opus 4.5 Pro
Gap to leader
19.4
points

Score distribution

The chart shows the top 10 models on AIME 2025, with Llama 3.1 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 3.1 Instruct sits at #220 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 19.4 points. The median model in this index scores 67.6, which puts Llama 3.1 Instruct above the midpoint.

Meta AI models average 62.6 on this benchmark. Llama 3.1 Instruct is 9.4 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 73.9. Llama 3.1 Instruct is 1.9 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 72.0 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 $4.05 per million input tokens, Llama 3.1 Instruct is above 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
Qwen3-Coder Instruct Alibaba Cloud 128000 $4.66 78.1
Reka Core Reka AI 32768 $12.17 77.4
GPT-5.2 Nano OpenAI 128000 $9.73 73.5
Llama 3 Novita Chat Novita AI 65536 $3.50 74.2
Llama 3.1 Instruct Meta AI 200000 $4.05 75.7
Nemotron 4 NVIDIA 65536 $4.18 76.6
GLM-4.6 Base Zhipu AI 128000 $4.53 78.5

Other benchmarks for Llama 3.1 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.5 196 67th
GPQA Diamond 71.8 223 63th
SWE-bench Verified 64.2 229 62th
HumanEval 81.2 209 65th
MATH-500 77.0 278 54th
LiveCodeBench 67.0 252 58th
IFEval 85.5 174 71th
TruthfulQA 79.0 217 64th
HellaSwag 84.9 252 58th
MMMU 70.9 274 54th
Arena Elo 1395.5 226 62th

FAQ

What score does Llama 3.1 Instruct get on AIME 2025?

Llama 3.1 Instruct scores 72.0 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.

How does Llama 3.1 Instruct rank on AIME 2025?

It ranks #220 of 600 models, in the 63rd percentile. The leader is Claude Opus 4.5 Pro at 91.4.

Is Llama 3.1 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 3.1 Instruct cost?

Llama 3.1 Instruct costs $4.05 per million input tokens and $16.24 per million output tokens.

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