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

4 is the maximum. Remove one to add another.

glm-5.3 vs perceptron-mk1.5 vs muse-spark-1.3 vs muse-spark-open
AttributeGLM 5.3glm-5.3Perceptron Mk1.5perceptron-mk1.5Muse Spark 1.3muse-spark-1.3Muse Spark Openmuse-spark-open
Pricing
Input$1.40 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Output$4.40 / 1M$1.50 / 1M$4.25 / 1M$4.25 / 1M
Cache Write (5m)$1.40 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Cache Write (1h)$1.40 / 1M$0.15 / 1M$1.25 / 1M$1.25 / 1M
Cache Read$1.40 / 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
VisionNoNoYesYes
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 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.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.