Comparison · Updated Sep 19, 2026
Llama 4 vs DeepSeek V3
The two most-deployed open-weight families of 2025: Llama 4 offers an enormous context window and a broad ecosystem, DeepSeek V3 delivers strong reasoning per dollar.
At a glance
| Spec | Llama 4 | DeepSeek V3 |
|---|---|---|
| Released | Apr 5, 2025 | Dec 26, 2024 |
| Context window | 10M tokens | 128K tokens |
| Licence | Open weights | Open weights |
| Inputs | text, image | text |
| Public API | No | Yes |
Model A
Llama 4
Meta's Llama 4 MoE family with very long context and multimodal input.
Apr 5, 2025
Model B
DeepSeek V3
671B MoE open-weight base model.
Dec 26, 2024
Differences
| Attribute | Llama 4 | DeepSeek V3 |
|---|---|---|
| Released | April 2025 | December 2024 |
| Licence | Open weights (Llama licence) | Open weights |
| Context window | Up to 10M tokens | 128K tokens |
| Architecture | Mixture of experts | Mixture of experts |
| Ecosystem | Very broad | Good |
| Best for | Long context, wide tooling | Reasoning and code value |
Verdict
Llama 4 for ecosystem, tooling and very long context. DeepSeek V3 for the best open-weight reasoning and code value.
Analysis
Openness
Both ship downloadable weights, so both can be self-hosted, fine-tuned and run in private environments.
Context and architecture
Llama 4''s headline feature is its very large context window, useful for whole-corpus tasks. DeepSeek V3 uses a mixture-of-experts design that keeps inference cost low relative to its quality.
Tooling
Llama has the widest support across inference servers, quantisation tools and fine-tuning frameworks. DeepSeek support is good and improving.
Frequently asked
- Are both really open source?
- Both publish weights you can download and run. Llama 4 uses a community licence with conditions, so it is open-weight rather than strictly OSI open source.