Model comparison
Llama 4 Scout vs DeepSeek R1
Meta
Llama 4 Scout
Open-weights frontier with a headline 10M-token context.
DeepSeek
DeepSeek R1
The open-weights reasoning model that reset the cost curve.
Specs
| Metric | Llama 4 Scout | DeepSeek R1 |
|---|---|---|
| Context window | 328K tokens↑ | 64K tokens |
| Input $/1M tokens | $0.080↑ | $0.700 |
| Output $/1M tokens | $0.300↑ | $2.50 |
| Modalities | Text · Image | Text |
| Open weights | Yes | Yes |
| Released | Apr 2025 | Jan 2025 |
Capability differences
| Capability | Llama 4 Scout | DeepSeek R1 |
|---|---|---|
| Tool use | Yes | No |
| Vision | Yes | No |
| Extended thinking | No | Yes |
Key differences
- -Llama 4 Scout offers 328K context; DeepSeek R1 offers 64K.
- -Input pricing: Llama 4 Scout at $0.080/1M vs DeepSeek R1 at $0.700/1M.