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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 5.3 FlashZ.AIRemove
  2. Command ACohereRemove
  3. GLM 5.3Z.AIRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

glm-5.3-flash vs command-a vs glm-5.3 vs deepseek-v4.1-flash
AttributeGLM 5.3 Flashglm-5.3-flashCommand Acommand-aGLM 5.3glm-5.3DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.075 / 1M$2.50 / 1M$1.40 / 1M$0.30 / 1M
Output$0.25 / 1M$10.00 / 1M$4.40 / 1M$1.20 / 1M
Cache Write (5m)$0.075 / 1M$2.50 / 1M$1.40 / 1M$0.30 / 1M
Cache Write (1h)$0.075 / 1M$2.50 / 1M$1.40 / 1M$0.30 / 1M
Cache Read$0.075 / 1M$2.50 / 1M$1.40 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M256K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoNoYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderZ.AICohereZ.AIDeepSeek
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-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.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.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.