DeepSeek V4 vs GLM-5

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.	GLM-5 Zhipu AI's MIT-licensed 744B-parameter MoE model targeting complex systems engineering and agentic tasks.
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	+ MIT-licensed open weights + Designed specifically for agentic and tool-use workloads + Sparse attention architecture reduces long-context serving cost + 40B active parameters keep inference cost moderate for its class
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	− 744B total parameters still demand multi-GPU infrastructure to self-host − Smaller first-party API ecosystem than DeepSeek or Alibaba
Used in stacks	0	0