Mathematics · Anyscale

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

Llama 3 Anyscale Instruct scores 74.5 on AIME 2025, placing it #165 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
74.5
0–100 scale
Rank
#165
of 600
Percentile
73th
within the index
Benchmark avg
63.6
all models
Leader
91.4
Claude Opus 4.5 Pro
Gap to leader
16.9
points

Score distribution

The chart shows the top 10 models on AIME 2025, with Llama 3 Anyscale 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 Anyscale Instruct sits at #165 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 16.9 points. The median model in this index scores 67.6, which puts Llama 3 Anyscale Instruct above the midpoint.

Anyscale models average 59.1 on this benchmark. Llama 3 Anyscale Instruct is 15.4 points above that provider line, so it is a stronger result than the average Anyscale model.

Among multimodal models, the average is 73.9. Llama 3 Anyscale Instruct is 0.6 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 74.5 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 Anyscale 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
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0
Sonar Pro Perplexity 128000 $13.01 79.1
Reka Core Max Reka AI 128000 $13.41 79.3
GLM-4.6 Instruct Zhipu AI 1000000 $5.15 80.4
Llama 3 Anyscale Instruct Anyscale 200000 $3.91 75.7
Qwen3 Alibaba Cloud 128000 $5.04 80.3
DeepSeek-V3.2 Base DeepSeek 128000 $5.05 80.2

Other benchmarks for Llama 3 Anyscale Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.9 280 53th
GPQA Diamond 73.4 190 68th
SWE-bench Verified 61.4 293 51th
HumanEval 77.9 289 52th
MATH-500 79.6 218 64th
LiveCodeBench 71.4 161 73th
IFEval 83.5 228 62th
TruthfulQA 79.5 201 67th
HellaSwag 85.2 233 61th
MMMU 69.8 310 48th
Arena Elo 1391.8 241 60th

FAQ

What score does Llama 3 Anyscale Instruct get on AIME 2025?

Llama 3 Anyscale Instruct scores 74.5 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.

How does Llama 3 Anyscale Instruct rank on AIME 2025?

It ranks #165 of 600 models, in the 73rd percentile. The leader is Claude Opus 4.5 Pro at 91.4.

Is Llama 3 Anyscale 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 Anyscale Instruct cost?

Llama 3 Anyscale Instruct costs $3.91 per million input tokens and $14.49 per million output tokens.

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