Model comparison
Llama 4 Scout vs DeepSeek-V3
- Input
- $0.18
- Output
- $0.59
- Context
- 10M
- Released
- 2025-04-05
- Input
- $0.27 / 1M tokens (cache miss)
- Output
- $1.10 / 1M tokens
- Context
- 128K tokens
- Released
- 2024-12-26
DeepSeek-V3 scores higher on 3 of the 3 benchmarks both models report; Llama 4 Scout is cheaper on input tokens ($0.2 vs $0.3 per 1M, 1.5×); Llama 4 Scout has the larger context window (10M vs 128K).
Specs and pricing side by side
| Spec | Llama 4 Scout | DeepSeek-V3 |
|---|---|---|
| Maker | Meta | DeepSeek |
| Released | 2025-04-05 | 2024-12-26 |
| Context window | 10M | 128K tokens |
| Input price | $0.18 | $0.27 / 1M tokens (cache miss) |
| Output price | $0.59 | $1.10 / 1M tokens |
| Parameters | 109B total · 17B active (16 experts) | 671B total / 37B active per token (Mixture-of-Experts) |
| License | Llama 4 Community License Agreement | DeepSeek Model License (commercial use permitted); code under MIT |
| Weights | Open weights | Open weightssame |
| Modalities | Text, Vision | text |
| Knowledge cutoff | 2024-08 | not published |
Not published by either maker: max output.
Benchmarks both models report
| Benchmark | Llama 4 Scout | DeepSeek-V3 |
|---|---|---|
| MMLU Pro | 74.3% | 75.9% |
| GPQA Diamond | 57.2% | 59.1% |
| LiveCodeBench | 32.8% | 37.6% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Llama 4 Scout if…
- Cost matters: input tokens cost 1.5× less ($0.2 vs $0.3 per 1M).
- You need the longer context (10M vs 128K).
- You need Text / Vision input, which DeepSeek-V3 lacks.
- Your use case is: long-document and large-codebase analysis at up to 10M-token context.
Pick DeepSeek-V3 if…
- You care about MMLU Pro, GPQA Diamond, LiveCodeBench (it scores higher on 3 shared benchmarks).
- You need text input, which Llama 4 Scout lacks.
- Your use case is: general-purpose chat and instruction following at low cost.
FAQ
Which is better, Llama 4 Scout or DeepSeek-V3?
DeepSeek-V3 scores higher on 3 of the 3 benchmarks both models report; Llama 4 Scout is cheaper on input tokens ($0.2 vs $0.3 per 1M, 1.5×); Llama 4 Scout has the larger context window (10M vs 128K). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Llama 4 Scout?
Llama 4 Scout: $0.18 input, $0.59 output. DeepSeek-V3: $0.27 / 1M tokens (cache miss) input, $1.10 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Llama 4 Scout and DeepSeek-V3?
Llama 4 Scout offers 10M; DeepSeek-V3 offers 128K tokens.
Is Llama 4 Scout newer than DeepSeek-V3?
Llama 4 Scout was released 2025-04-05; DeepSeek-V3 was released 2024-12-26.