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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 5.3Z.AIRemove
  2. Command R (08-2024)CohereRemove
  3. GLM 5.3 FlashZ.AIRemove
glm-5.3 vs command-r-08-2024 vs glm-5.3-flash
AttributeGLM 5.3glm-5.3Command R (08-2024)command-r-08-2024GLM 5.3 Flashglm-5.3-flash
Pricing
Input$1.40 / 1M$0.1425 / 1M$0.075 / 1M
Output$4.40 / 1M$0.57 / 1M$0.25 / 1M
Cache Write (5m)$1.40 / 1M$0.1425 / 1M$0.075 / 1M
Cache Write (1h)$1.40 / 1M$0.1425 / 1M$0.075 / 1M
Cache Read$1.40 / 1M$0.1425 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M128K1M
Max outputN/AN/AN/A
Capabilities
VisionNoNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderZ.AICohereZ.AI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
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.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.