Meta
Llama 4 Scout is a Meta Llama 4 family model, from Meta's open-weight generation focused on multimodal intelligence and broad developer deployment. This page shows how the benchmarked variant ranks against hosted frontier models and other open-weight systems across quality, speed, and price context.
Introducing Llama 4Rank #429 across 526
Rank #375 across 436
Rank #98 across 357
Percentile score by analysis domain.
* Cost is inverted: lower input, output, and blended prices rank higher.
Higher bars mean stronger relative placement.
| Metric | Domain | Value | Rank |
|---|---|---|---|
| Artificial Analysis Intelligence Index | overall | 10.0 | #429 |
| Artificial Analysis Coding Index | coding | 6.7 | #375 |
| Artificial Analysis Math Index | math | 14.0 | #221 |
| MMLU-Pro | reasoning | 75.2% | #175 |
| reasoning |
| 58.7% |
| #307 |
| Humanity's Last Exam | reasoning | 4.3% | #397 |
| LiveCodeBench | coding | 29.9% | #222 |
| SciCode | coding, reasoning | 17.0% | #408 |
| MATH-500 | math | 84.4% | #98 |
| AIME | math | 28.3% | #88 |
| Output Speed | speed | 107.8 tok/s | #126 |
| Time to First Token | speed | 0.60s | #68 |
| Blended Price | cost | $0.292/M | #98 |
| Input Price | cost | $0.170/M | #94 |
| Output Price | cost | $0.660/M | #109 |
| Value Index | cost, overall | 34.2 | #156 |