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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 5.3Z.AIRemove
  2. GLM 5.3 FlashZ.AIRemove
  3. Muse Spark OpenMetaRemove
  4. Gemini 3.5 TranscribeGoogleRemove

4 is the maximum. Remove one to add another.

glm-5.3 vs glm-5.3-flash vs muse-spark-open vs gemini-3.5-transcribe
AttributeGLM 5.3glm-5.3GLM 5.3 Flashglm-5.3-flashMuse Spark Openmuse-spark-openGemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input$1.40 / 1M$0.075 / 1M$1.25 / 1M— Not priced per input token
Output$4.40 / 1M$0.25 / 1M$4.25 / 1M— Not priced per output token
Cache Write (5m)$1.40 / 1M$0.075 / 1M$1.25 / 1MNot applicable
Cache Write (1h)$1.40 / 1M$0.075 / 1M$1.25 / 1MNot applicable
Cache Read$1.40 / 1M$0.075 / 1M$1.25 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M98.3K
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderZ.AIZ.AIMetaGoogle
Categorychatchatchatvoice
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released———2026-09-25
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.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.