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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 001GoogleRemove
  2. Hy4 previewTencentRemove
  3. Gemini 3.8 FlashGoogleRemove
gemini-embedding-001 vs hy4-preview vs gemini-3.8-flash
AttributeGemini Embedding 001gemini-embedding-001Hy4 previewhy4-previewGemini 3.8 Flashgemini-3.8-flash
Pricing
Input$0.075 / 1M$0.834 / 1M$0.75 / 1M
Output$0.30 / 1M$2.50 / 1M$3.75 / 1M
Cache Write (5m)$0.075 / 1M$0.834 / 1M$0.75 / 1M
Cache Write (1h)$0.075 / 1M$0.834 / 1M$0.75 / 1M
Cache Read$0.075 / 1M$0.834 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context128K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleTencentGoogle
Categoryembeddingchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini-Embedding-001 is Google's high-quality text embedding model designed for semantic understanding and retrieval tasks. It converts text into dense vector representations optimized for semantic search, retrieval-augmented generation (RAG), clustering, classification, and recommendation systems. The model emphasizes strong multilingual performance, high semantic accuracy, and efficient embedding generation, making it well suited for large-scale knowledge indexing and production retrieval pipelines.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.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.