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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. Muse WonderMetaRemove
  2. Olmo 3 7B ThinkAllen AIRemove
  3. Muse Spark OpenMetaRemove
muse-wonder vs olmo-3-7b-think vs muse-spark-open
AttributeMuse Wondermuse-wonderOlmo 3 7B Thinkolmo-3-7b-thinkMuse Spark Openmuse-spark-open
Pricing
Input$4.00 / 1M$0.12 / 1M$1.25 / 1M
Output$20.00 / 1M$0.20 / 1M$4.25 / 1M
Cache Write (5m)$4.00 / 1M$0.12 / 1M$1.25 / 1M
Cache Write (1h)$4.00 / 1M$0.12 / 1M$1.25 / 1M
Cache Read$4.00 / 1M$0.12 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M65.5K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaAllen AIMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryMuse 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.Olmo 3 7B Think is a lightweight reasoning-focused model in the Olmo family, aimed at multi-step problem solving, logical inference, and instruction-driven tasks while keeping conversations coherent. Built by AI2 and released under Apache 2.0, it's fully open and well suited for both research and practical NLP 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.