DeepSeek V4 vs Kimi K2.6

Pick two tools from the same category to compare side-by-side.

	DeepSeek V4 DeepSeek's V4 generation of open-weight MoE models with 1M-token context and agent-focused reasoning modes.	Kimi K2.6 Moonshot AI's flagship 1T-parameter open-weight MoE model with native multimodal input and interleaved-thinking tool use.
Category	model	model
Vendor type	open source	open source
Pricing	free	free
Strengths	+ MIT-licensed open weights for both Pro and Flash variants + 1M-token context window + Selectable reasoning effort modes (non-think plus two thinking modes) + Sparse MoE design keeps activated parameters low relative to total size	+ Interleaved thinking with multi-step tool calling for agent workflows + 256K-token context window + Multimodal (image and video) input via built-in vision encoder + OpenAI/Anthropic-compatible first-party API eases drop-in adoption
Tradeoffs	− Branded as a preview release on deepseek.com as of June 2026 − V4-Pro's scale makes self-hosting impractical without large GPU clusters	− Modified MIT license (not plain MIT/Apache) requires review for some uses − Video chat is experimental and only available through the official API − 1T-parameter scale limits self-hosting to large deployments
Used in stacks	0	0