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Compare models

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-4o Audio PreviewOpenAIRemove
  3. GLM 5.3Z.AIRemove
  4. GLM 5.3 FlashZ.AIRemove

4 is the maximum. Remove one to add another.

hy4-preview vs gpt-4o-audio-preview vs glm-5.3 vs glm-5.3-flash
AttributeHy4 previewhy4-previewGPT-4o Audio Previewgpt-4o-audio-previewGLM 5.3glm-5.3GLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.834 / 1M$0.875 / 1M$1.40 / 1M$0.075 / 1M
Output$2.50 / 1M$3.50 / 1M$4.40 / 1M$0.25 / 1M
Cache Write (5m)$0.834 / 1MNot applicable$1.40 / 1M$0.075 / 1M
Cache Write (1h)$0.834 / 1MNot applicable$1.40 / 1M$0.075 / 1M
Cache Read$0.834 / 1MNot applicable$1.40 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M128K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoNoYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesYesYesYes
Catalogue
ProviderTencentOpenAIZ.AIZ.AI
Categorychatvoicechatchat
Charge typePay As You GoPay 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-4o-audio-preview adds support for audio inputs, allowing the model to understand nuances in audio recordings and enrich responses. It currently does not generate audio outputs, and audio input is billed per million audio tokens.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.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.