Llama 3 Anyscale Chat on AIME 2025: score, rank and what it means
Llama 3 Anyscale Chat scores 72.9 on AIME 2025, placing it #205 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 distribution
The chart shows the top 10 models on AIME 2025, with Llama 3 Anyscale Chat highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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 Chat sits at #205 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 18.5 points. The median model in this index scores 67.6, which puts Llama 3 Anyscale Chat above the midpoint.
Anyscale models average 59.1 on this benchmark. Llama 3 Anyscale Chat is 13.8 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 Chat is 1.0 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 72.9 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 $3.67 per million input tokens, Llama 3 Anyscale Chat 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Qwen3-Max Mini | Alibaba Cloud | 128000 | $11.13 | 76.5 |
| Llama 3.1 Turbo Chat | Together AI | 200000 | $3.95 | 76.1 |
| Nemotron 4 Chat | NVIDIA | 65536 | $3.99 | 75.0 |
| Kimi K1.5 Base | Moonshot AI | 65536 | $4.34 | 77.4 |
| Llama 3 Anyscale Chat | Anyscale | 65536 | $3.67 | 74.6 |
| Reka Flash Turbo | Reka AI | 128000 | $10.19 | 75.1 |
| ERNIE 4.0 Turbo | Baidu | 65536 | $12.00 | 78.0 |
Other benchmarks for Llama 3 Anyscale Chat
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 77.5 | 258 | 57th | |
| GPQA Diamond | 68.8 | 302 | 50th | |
| SWE-bench Verified | 61.8 | 283 | 53th | |
| HumanEval | 79.5 | 247 | 59th | |
| MATH-500 | 76.0 | 299 | 50th | |
| LiveCodeBench | 66.3 | 268 | 55th | |
| IFEval | 84.2 | 210 | 65th | |
| TruthfulQA | 75.9 | 308 | 49th | |
| HellaSwag | 85.1 | 238 | 60th | |
| MMMU | 72.6 | 230 | 62th | |
| Arena Elo | 1373.6 | 302 | 50th |
FAQ
What score does Llama 3 Anyscale Chat get on AIME 2025?
Llama 3 Anyscale Chat scores 72.9 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.
How does Llama 3 Anyscale Chat rank on AIME 2025?
It ranks #205 of 600 models, in the 66th percentile. The leader is Claude Opus 4.5 Pro at 91.4.
Is Llama 3 Anyscale Chat 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 Chat cost?
Llama 3 Anyscale Chat costs $3.67 per million input tokens and $14.56 per million output tokens.