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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. GLM 5.3Z.AIRemove
  2. Hy4 previewTencentRemove
  3. GPT Image 2OpenAIRemove
glm-5.3 vs hy4-preview vs gpt-image-2
AttributeGLM 5.3glm-5.3Hy4 previewhy4-previewGPT Image 2gpt-image-2
Pricing
Input$1.40 / 1M$0.834 / 1M
Output$4.40 / 1M$2.50 / 1M
Cache Write (5m)$1.40 / 1M$0.834 / 1MNot applicable
Cache Write (1h)$1.40 / 1M$0.834 / 1MNot applicable
Cache Read$1.40 / 1M$0.834 / 1MNot applicable
Web Search$0 / 1M$0 / 1M
Request$0.04 / request
BillingPay Per Request
Context
Max context1M1M272K
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderZ.AITencentOpenAI
Categorychatchatimage
Charge typePay As You GoPay As You GoPay Per Request
Released
Description
SummaryGLM-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.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.GPT Image 2 combines OpenAI's GPT-5.4 with advanced image generation capabilities from GPT Image 2, enabling fully integrated multimodal workflows. It allows users to seamlessly transition between reasoning, coding, and visual generation within a single interaction, making it well suited for creative, development, and agent-driven applications that require both intelligence and visual output.