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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. GLM 5.3Z.AIRemove
  3. Gemini 3 Flash PreviewGoogleRemove
hy4-preview vs glm-5.3 vs gemini-3-flash-preview
AttributeHy4 previewhy4-previewGLM 5.3glm-5.3Gemini 3 Flash Previewgemini-3-flash-preview
Pricing
Input$0.834 / 1M$1.40 / 1M$0.25 / 1M
Output$2.50 / 1M$4.40 / 1M$1.50 / 1M
Cache Write (5m)$0.834 / 1M$1.40 / 1M$0.25 / 1M
Cache Write (1h)$0.834 / 1M$1.40 / 1M$0.25 / 1M
Cache Read$0.834 / 1M$1.40 / 1M$0.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1.0M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderTencentZ.AIGoogle
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.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.Gemini 3 Flash Preview is a fast, cost-efficient reasoning model designed for agent workflows, multi-turn chat, and coding assistance. It offers near-Pro level reasoning and tool-use performance with significantly lower latency than larger Gemini models, making it ideal for interactive development and long-running agent loops. It improves on Gemini 2.5 Flash with stronger reasoning, multimodal understanding, and reliability. The model supports a 1M-token context window and multimodal inputs (text, images, audio, video, PDFs) with text outputs. It provides configurable reasoning levels, structured output formats, tool use, and automatic context caching—optimized for users seeking strong agentic reasoning without the cost or latency of full frontier-scale models.