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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Gemini Embedding 2GoogleRemove
  2. Gemini 3.8 FlashGoogleRemove
gemini-embedding-2-preview vs gemini-3.8-flash
AttributeGemini Embedding 2gemini-embedding-2-previewGemini 3.8 Flashgemini-3.8-flash
Pricing
Input$0.60 / 1M$0.75 / 1M
Output$2.40 / 1M$3.75 / 1M
Cache Write (5m)$0.60 / 1M$0.75 / 1M
Cache Write (1h)$0.60 / 1M$0.75 / 1M
Cache Read$0.60 / 1M$0.75 / 1M
Web Search$0 / 1M
Context
Max context8.2K1M
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeNoYes
StreamingNoYes
Catalogue
ProviderGoogleGoogle
Categoryembeddingchat
Charge typePay As You GoPay As You Go
Released
Description
SummaryGemini Embedding 2 is Google's advanced text embedding model designed for high-accuracy semantic representation across large-scale retrieval and understanding tasks. It converts text into dense vector embeddings optimized for semantic search, retrieval-augmented generation (RAG), clustering, classification, and recommendation systems. Built for production use, it offers strong multilingual support, improved semantic similarity accuracy, and efficient embedding generation, making it well suited for large knowledge indexing pipelines and enterprise-scale retrieval applications.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.