# DeepSeek V4.1 Flash vs Llama 4 Scout

On provider list prices, DeepSeek V4.1 Flash costs $0.15 per million input tokens against $0.18 for Llama 4 Scout: 1.2x apart. Output is $0.60 against $0.59.

## Specifications

| | DeepSeek V4.1 Flash | Llama 4 Scout |
| --- | --- | --- |
| Lab | Deepseek | Meta |
| Access | Open weights | Open weights |
| Context window | 1M tokens | 1M tokens |
| List price, input | $0.15 / M tokens | $0.18 / M tokens |
| List price, output | $0.60 / M tokens | $0.59 / M tokens |
| Cached input | n/a | n/a |
| License | Not listed | Llama community |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.

## What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $390 a month on DeepSeek V4.1 Flash and $422.50 on Llama 4 Scout at list: a gap of $32.50.

## Choose DeepSeek V4.1 Flash for

- The lower list price ($0.15 in / $0.60 out per M tokens)

## Choose Llama 4 Scout for

- Whole-document reasoning
- High-volume extraction
- Fine-tuning under the Llama 4 license

## Common questions

### Which is cheaper, DeepSeek V4.1 Flash or Llama 4 Scout?

DeepSeek V4.1 Flash, on this workload shape. At list prices it is $0.15/$0.60 per million tokens in and out against $0.18/$0.59 for Llama 4 Scout. Billed on Allocate: $0.16/$0.64 against $0.19/$0.63.

### Which has the bigger context window?

They match: both read 1,048,576 tokens (1M) per request.

### Can I fine-tune DeepSeek V4.1 Flash or Llama 4 Scout?

Both publish open weights (DeepSeek V4.1 Flash: Not listed; Llama 4 Scout: Llama community), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

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[HTML page](https://allocate.network/compare/deepseek-deepseek-v4-1-flash-vs-meta-llama-4-scout-17b-16e-instruct) · [DeepSeek V4.1 Flash](https://allocate.network/models/deepseek-deepseek-v4-1-flash.md) · [Llama 4 Scout](https://allocate.network/models/meta-llama-4-scout-17b-16e-instruct.md) · [Machine-readable catalog](https://allocate.network/catalog.json)