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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. GLM 5.3 FlashZ.AIRemove
  3. Grok 4 FastxAIRemove
glm-5.3 vs glm-5.3-flash vs grok-4-fast
AttributeGLM 5.3glm-5.3GLM 5.3 Flashglm-5.3-flashGrok 4 Fastgrok-4-fast
Pricing
Input$1.40 / 1M$0.075 / 1M$0.07 / 1M
Output$4.40 / 1M$0.25 / 1M$0.175 / 1M
Cache Write (5m)$1.40 / 1M$0.075 / 1M$0.07 / 1M
Cache Write (1h)$1.40 / 1M$0.075 / 1M$0.07 / 1M
Cache Read$1.40 / 1M$0.075 / 1M$0.07 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M2M
Max outputN/AN/AN/A
Capabilities
VisionNoYesNo
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderZ.AIZ.AIxAI
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.Grok 4 Fast is xAI's cost-efficient multimodal model with a massive 2M-token context window. It’s available in both reasoning and non-reasoning modes, allowing developers to toggle deeper thinking when needed. Designed for scalable performance, it balances speed, capability, and price — with reasoning controllable via the reasoning_enabled API parameter.