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Kimi vs DeepSeek

Kimi and DeepSeek side by side: model sizes, the VRAM you need, context window, abilities, licence and which one to pick.

Side by side

KimiDeepSeek
TypeOpen-weight modelsOpen-weight models
DeveloperMoonshot AIDeepSeek
Newest modelKimi K3.1 Pro · Nov 2026DeepSeek-V4.1 Flash · Sep 2026
SizesCloud-size onlyCloud-size only
Smallest VRAM (4-bit)Data-centre GPUsData-centre GPUs
Context window——
AbilitiesTool callingReasoning modeImage inputTool callingReasoning modeImage input
LicenceKimi K3.1 Pro License, Kimi K3 License, Modified MITMIT
Run itollama run kimi-k3.1-pro:cloudollama run deepseek-v4.1-flash:cloud

Which one should you pick?

  • DeepSeek has the simpler licence for commercial use (Apache 2.0 or MIT).

Pick Kimi if…

  • you want the strongest open model and will run it hosted
  • you need agentic coding with very long context

Pick DeepSeek if…

  • you need an MIT-licensed frontier model to self-host
  • you want visible step-by-step reasoning (R1)
  • you need a 1M-token context in an open model

Frequently asked questions

Is Kimi better than DeepSeek?

It depends on the job and your hardware. DeepSeek has the simpler licence for commercial use (Apache 2.0 or MIT). For quality, test both on your own prompts: benchmark rankings change with every release.

Can I use Kimi and DeepSeek commercially?

Kimi: Kimi K3.1 Pro License, Kimi K3 License, Modified MIT. DeepSeek: MIT. Check the exact licence of the model you deploy; custom licences can limit very large companies or certain uses.

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