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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. GLM 4.7 FlashZ.AIRemove
  2. GLM 5.3 FlashZ.AIRemove
  3. GPT-6 AstraOpenAIRemove
glm-4.7-flash vs glm-5.3-flash vs gpt-6-astra
AttributeGLM 4.7 Flashglm-4.7-flashGLM 5.3 Flashglm-5.3-flashGPT-6 Astragpt-6-astra
Pricing
Input$0.06 / 1M$0.075 / 1M$10.00 / 1M
Output$0.40 / 1M$0.25 / 1M$50.00 / 1M
Cache Write (5m)$0.06 / 1M$0.075 / 1M$10.00 / 1M
Cache Write (1h)$0.06 / 1M$0.075 / 1M$10.00 / 1M
Cache Read$0.06 / 1M$0.075 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context200K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderZ.AIZ.AIOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-4.7-Flash is a state-of-the-art 30B-class model designed to strike a strong balance between performance and efficiency. It is specifically optimized for agentic coding scenarios, with enhanced capabilities in code generation, long-horizon task planning, and tool-based collaboration. Among open-source models of comparable size, GLM-4.7-Flash has achieved leading results on multiple public benchmark leaderboards, establishing itself as a competitive and practical choice for advanced developer and agent workflows.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.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.