Llama 4 Scout vs Llama 4 Maverick — Meta’s two Llama 4 variants compared. Below is the full side-by-side: specifications, API pricing, context window, local hardware requirements, and a clear, data-driven recommendation on which to pick.
| Spec | Llama 4 Scout | Llama 4 Maverick |
|---|---|---|
| Developer | Meta | Meta |
| Type | Multimodal (MoE) | Multimodal (MoE) |
| Parameters | 109B total / 17B active (MoE) | 400B total / 17B active (MoE) |
| Context window | 10M | 1M |
| Modality | Text, Image → Text | Text, Image → Text |
| License | Llama 4 Community (EU-restricted) | Llama 4 Community (EU-restricted) |
| Open weights | ✅ Yes | ✅ Yes |
| Input price ($/1M) | $0.1 | $0.15 |
| Output price ($/1M) | $0.3 | $0.6 |
| VRAM (4-bit) | ~65 GB | ~240 GB |
| Min GPU (local) | H100 80GB / Mac 128GB | Multi-GPU server |
| Released | 2025 | 2025 |
Key differences
- Cost: Llama 4 Scout is 75% cheaper than Llama 4 Maverick on a blended-token basis.
- Context: Llama 4 Scout wins on context window (10M vs 1M) — better for long documents, large codebases and big RAG inputs.
- Openness: both are open-weight, so either can be self-hosted or fine-tuned. Compare their VRAM needs above to see what your GPU can run.
- Run Llama 4 Scout locally: ~~65 GB at 4-bit (min H100 80GB / Mac 128GB).
- Run Llama 4 Maverick locally: ~~240 GB at 4-bit (min Multi-GPU server).
Which should you choose?
Choose Llama 4 Scout if you want the lower per-token cost for high-volume workloads, or you need the larger context window.
Choose Llama 4 Maverick if it fits your existing stack or you prefer Meta.
→ Estimate real costs in the API cost calculator · check local hardware in the VRAM calculator · browse all 30+ models.
All specs and prices are pulled live from our AI models database and kept current. Compare either model against others, or estimate your own monthly spend with the free calculators above.