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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. mai-ds-r1:freeNot in the catalogueRemove
  2. Muse Spark OpenMetaRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Muse Spark 1.3MetaRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs muse-spark-open vs perceptron-mk1.5 vs muse-spark-1.3
Attributemai-ds-r1:freeNot in the catalogueMuse Spark Openmuse-spark-openPerceptron Mk1.5perceptron-mk1.5Muse Spark 1.3muse-spark-1.3
Pricing
Input—$1.25 / 1M$0.15 / 1M$1.25 / 1M
Output—$4.25 / 1M$1.50 / 1M$4.25 / 1M
Cache Write (5m)—$1.25 / 1M$0.15 / 1M$1.25 / 1M
Cache Write (1h)—$1.25 / 1M$0.15 / 1M$1.25 / 1M
Cache Read—$1.25 / 1M$0.15 / 1M$1.25 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context—1M36.9K1M
Max output—N/AN/AN/A
Capabilities
Vision—YesNoYes
Function Calling—YesNoYes
JSON Mode—YesNoYes
Streaming—YesYesYes
Catalogue
Provider—MetaPerceptronMeta
Category—chatchatchat
Charge type—Pay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
Summary—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.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.