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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. Hy4 previewTencentRemove
  2. GPT-5.6 Terra ProOpenAIRemove
  3. Gemini 3.8 FlashGoogleRemove
hy4-preview vs gpt-5.6-terra-pro vs gemini-3.8-flash
AttributeHy4 previewhy4-previewGPT-5.6 Terra Progpt-5.6-terra-proGemini 3.8 Flashgemini-3.8-flash
Pricing
Input$0.834 / 1M$2.00 / 1M$0.75 / 1M
Output$2.50 / 1M$12.00 / 1M$3.75 / 1M
Cache Write (5m)$0.834 / 1M$2.00 / 1M$0.75 / 1M
Cache Write (1h)$0.834 / 1M$2.00 / 1M$0.75 / 1M
Cache Read$0.834 / 1M$2.00 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderTencentOpenAIGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryTencent 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.GPT-5.6 Terra Pro uses the same underlying model as GPT-5.6 Terra, but runs with reasoning.mode set to pro to deliver higher-quality responses on complex tasks. Optimized for deeper reasoning and greater reliability, it is well suited for advanced coding, multi-step reasoning, and agentic workflows where improved accuracy and solution quality are more important than maximizing speed or minimizing cost.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.