DeepSeek V4 vs OpenAI text-embedding-3-large

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.	OpenAI text-embedding-3-large OpenAI's most capable embedding model for English and non-English retrieval, served via usage-priced API.
Category	model	model
Vendor type	open source	commercial
Pricing	free	usage
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	+ Strong general-purpose retrieval quality across English and non-English text + Ubiquitous ecosystem support in vector databases and RAG frameworks + Simple usage-based pricing with a cheaper small variant for cost-sensitive paths
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	− API-only (no open weights or on-prem option) − General-purpose model with no domain-specialized variants, unlike some competitors
Used in stacks	0	0