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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. GLM 5.3Z.AIRemove
  3. Muse Spark 1.3MetaRemove
  4. Qwen3 235B A22BAlibabaRemove

4 is the maximum. Remove one to add another.

glm-5.3-flash vs glm-5.3 vs muse-spark-1.3 vs qwen3-235b-a22b
AttributeGLM 5.3 Flashglm-5.3-flashGLM 5.3glm-5.3Muse Spark 1.3muse-spark-1.3Qwen3 235B A22Bqwen3-235b-a22b
Pricing
Input$0.075 / 1M$1.40 / 1M$1.25 / 1M$0.20 / 1M
Output$0.25 / 1M$4.40 / 1M$4.25 / 1M$0.60 / 1M
Cache Write (5m)$0.075 / 1M$1.40 / 1M$1.25 / 1M$0.20 / 1M
Cache Write (1h)$0.075 / 1M$1.40 / 1M$1.25 / 1M$0.20 / 1M
Cache Read$0.075 / 1M$1.40 / 1M$1.25 / 1M$0.20 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M41.0K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderZ.AIZ.AIMetaAlibaba
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.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.