Llama 4 Maverick and DeepSeek V3.2 are both open-weight, MoE-based and self-hostable, but they emphasise different things. Maverick is Meta's natively multimodal flagship — 400B total (17B active), a 1M-token context and image understanding — that beat GPT-4o and Gemini 2.0 Flash on Arena at launch. It's the open choice when you need multimodality and a huge context.
DeepSeek V3.2 is the text/code efficiency specialist: sparse attention, strong reasoning-in-tool-use and lower pricing, but no native image input. Maverick wins on multimodality and context size; DeepSeek wins on cost-efficient reasoning and coding value. For multimodal open deployments, Maverick leads; for cheap, high-volume text and code, DeepSeek is the better fit.
Which should you choose?
The verdict
Llama 4 Maverick wins on multimodality and context length; DeepSeek V3.2 wins on cost-efficient text and code reasoning. Choose by whether you need images or maximum value.
Watch the comparison
Llama 4 Maverick vs DeepSeek V3.2 — video reviews on YouTubeWatch hands-on tests and side-by-side demosFrequently asked questions
Is Llama 4 Maverick multimodal?
Yes — it natively handles text and images, while DeepSeek V3.2 focuses on text and code.
Which has the bigger context?
Maverick, with a 1M-token window versus DeepSeek's 128K.