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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. Perceptron Mk1.5PerceptronRemove
  3. Muse Spark 1.3MetaRemove
  4. Muse Spark OpenMetaRemove

4 is the maximum. Remove one to add another.

glm-5.3-flash vs perceptron-mk1.5 vs muse-spark-1.3 vs muse-spark-open
AttributeGLM 5.3 Flashglm-5.3-flashPerceptron Mk1.5perceptron-mk1.5Muse Spark 1.3muse-spark-1.3Muse Spark Openmuse-spark-open
Pricing
Input$0.075 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Output$0.25 / 1M$1.50 / 1M$4.25 / 1M$4.25 / 1M
Cache Write (5m)$0.075 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Cache Write (1h)$0.075 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Cache Read$0.075 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M36.9K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesYesYesYes
Catalogue
ProviderZ.AIPerceptronMetaMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-25——
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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.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.