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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. mai-ds-r1:freeNot in the catalogueRemove
  2. Muse WonderMetaRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. GPT-6 Astra ProOpenAIRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs muse-wonder vs perceptron-mk1.5 vs gpt-6-astra-pro
Attributemai-ds-r1:freeNot in the catalogueMuse Wondermuse-wonderPerceptron Mk1.5perceptron-mk1.5GPT-6 Astra Progpt-6-astra-pro
Pricing
Input—$4.00 / 1M$0.15 / 1M$10.00 / 1M
Output—$20.00 / 1M$1.50 / 1M$50.00 / 1M
Cache Write (5m)—$4.00 / 1M$0.15 / 1M$10.00 / 1M
Cache Write (1h)—$4.00 / 1M$0.15 / 1M$10.00 / 1M
Cache Read—$4.00 / 1M$0.15 / 1M$10.00 / 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—MetaPerceptronOpenAI
Category—chatchatchat
Charge type—Pay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
Summary—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.GPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.