Llama 4 Scout Instruct on AIME 2025: score, rank and what it means
Llama 4 Scout Instruct scores 77.3 on AIME 2025, placing it #125 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 4 Scout Instruct 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 4 Scout Instruct sits at #125 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 14.1 points. The median model in this index scores 67.6, which puts Llama 4 Scout Instruct above the midpoint.
Meta AI models average 62.6 on this benchmark. Llama 4 Scout Instruct is 14.7 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 4 Scout Instruct is 3.4 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 77.3 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 $4.59 per million input tokens, Llama 4 Scout 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Gemini 3 Pro Mini | Google DeepMind | 128000 | $12.27 | 78.1 |
| GPT-4.1 Turbo | OpenAI | 1000000 | $16.12 | 82.9 |
| Hunyuan-Turbo Reasoning | Tencent | 128000 | $11.89 | 77.5 |
| Kimi K2 Instruct | Moonshot AI | 1000000 | $5.80 | 82.3 |
| Llama 4 Scout Instruct | Meta AI | 32768 | $4.59 | 79.1 |
| Command A Max | Cohere | 400000 | $14.28 | 79.9 |
| ERNIE 4.0 Reasoning | Baidu | 65536 | $12.20 | 77.8 |
Other benchmarks for Llama 4 Scout Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 80.0 | 183 | 70th | |
| GPQA Diamond | 76.1 | 121 | 80th | |
| SWE-bench Verified | 70.1 | 108 | 82th | |
| HumanEval | 81.6 | 194 | 68th | |
| MATH-500 | 84.7 | 114 | 81th | |
| LiveCodeBench | 73.8 | 113 | 81th | |
| IFEval | 85.2 | 185 | 69th | |
| TruthfulQA | 79.9 | 181 | 70th | |
| HellaSwag | 88.4 | 127 | 79th | |
| MMMU | 73.0 | 221 | 63th | |
| Arena Elo | 1429.1 | 122 | 80th |
FAQ
What score does Llama 4 Scout Instruct get on AIME 2025?
Llama 4 Scout Instruct scores 77.3 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.
How does Llama 4 Scout Instruct rank on AIME 2025?
It ranks #125 of 600 models, in the 79th percentile. The leader is Claude Opus 4.5 Pro at 91.4.
Is Llama 4 Scout 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 4 Scout Instruct cost?
Llama 4 Scout Instruct costs $4.59 per million input tokens and $20.15 per million output tokens.