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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-6 AstraOpenAIRemove
  3. DeepSeek R1 ZeroDeepSeekRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

hy4-preview vs gpt-6-astra vs deepseek-r1-zero vs glm-5.3
AttributeHy4 previewhy4-previewGPT-6 Astragpt-6-astraDeepSeek R1 Zerodeepseek-r1-zeroGLM 5.3glm-5.3
Pricing
Input$0.834 / 1M$10.00 / 1M$0 / 1M$1.40 / 1M
Output$2.50 / 1M$50.00 / 1M$0 / 1M$4.40 / 1M
Cache Write (5m)$0.834 / 1M$10.00 / 1M$0.00 / 1M$1.40 / 1M
Cache Write (1h)$0.834 / 1M$10.00 / 1M$0.00 / 1M$1.40 / 1M
Cache Read$0.834 / 1M$10.00 / 1M$0.00 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M163.8K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoNo
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderTencentOpenAIDeepSeekZ.AI
Categorychatchatchatchat
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-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.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.