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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. Muse Spark OpenMetaRemove
  2. Muse WonderMetaRemove
  3. Claude Fable 5.2AnthropicRemove
  4. MiniMax M3MiniMaxRemove

4 is the maximum. Remove one to add another.

muse-spark-open vs muse-wonder vs claude-fable-5.2 vs minimax-m3
AttributeMuse Spark Openmuse-spark-openMuse Wondermuse-wonderClaude Fable 5.2claude-fable-5.2MiniMax M3minimax-m3
Pricing
Input$1.25 / 1M$4.00 / 1M$8.00 / 1M$0.30 / 1M
Output$4.25 / 1M$20.00 / 1M$40.00 / 1M$1.20 / 1M
Cache Write (5m)$1.25 / 1M$4.00 / 1M$10.00 / 1M$0.30 / 1M
Cache Write (1h)$1.25 / 1M$4.00 / 1M$16.00 / 1M$0.30 / 1M
Cache Read$1.25 / 1M$4.00 / 1M$0.20 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderMetaMetaAnthropicMiniMax
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
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.Claude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges.MiniMax-M3 is a multimodal foundation model from MiniMax, supporting text, image, and video inputs with text output and a 1M-token context window. It is designed for long-horizon agentic workflows, coding, and tool-driven task execution, enabling sustained reasoning across complex tasks. Built on MiniMax Sparse Attention (MSA), the model dramatically improves long-context efficiency by replacing full attention with KV-block selection, reducing compute costs at 1M-token contexts while maintaining strong performance. Trained as a native multimodal model and optimized for multi-turn, production-style collaboration, MiniMax-M3 excels at extended, multi-step workflows rather than single-turn interactions.