Skip to content

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. Muse Spark OpenMetaRemove
  2. Muse WonderMetaRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. GLM 5Z.AIRemove

4 is the maximum. Remove one to add another.

muse-spark-open vs muse-wonder vs perceptron-mk1.5 vs glm-5
AttributeMuse Spark Openmuse-spark-openMuse Wondermuse-wonderPerceptron Mk1.5perceptron-mk1.5GLM 5glm-5
Pricing
Input$1.25 / 1M$4.00 / 1M$0.15 / 1M$0.60 / 1M
Output$4.25 / 1M$20.00 / 1M$1.50 / 1M$2.20 / 1M
Cache Write (5m)$1.25 / 1M$4.00 / 1M$0.15 / 1M$0.60 / 1M
Cache Write (1h)$1.25 / 1M$4.00 / 1M$0.15 / 1M$0.60 / 1M
Cache Read$1.25 / 1M$4.00 / 1M$0.15 / 1M$0.60 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K202.8K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesYesYes
Catalogue
ProviderMetaMetaPerceptronZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
SummaryMuse 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.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.GLM-5 is Z.AI's flagship open-source foundation model, engineered for complex systems design and long-horizon agent workflows. Built with expert developers in mind, it delivers production-grade performance on large-scale programming tasks, rivaling leading closed-source models. With strong agentic planning, deep backend reasoning, and iterative self-correction capabilities, GLM-5 extends beyond traditional code generation to support full-system construction and autonomous execution, making it well suited for advanced engineering and agent-driven development environments.