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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. mai-ds-r1:freeNot in the catalogueRemove
  3. Gemini 3.1 Flash Lite Image (Google AI Studio)GoogleEnterprise & partner accessRemove
muse-wonder vs mai-ds-r1:free vs gemini-3.1-flash-lite-image-aistudio
AttributeMuse Wondermuse-wondermai-ds-r1:freeNot in the catalogueGemini 3.1 Flash Lite Image (Google AI Studio)gemini-3.1-flash-lite-image-aistudio
Pricing
Input$4.00 / 1M——
Output$20.00 / 1M——
Cache Write (5m)$4.00 / 1M—Not applicable
Cache Write (1h)$4.00 / 1M—Not applicable
Cache Read$4.00 / 1M—Not applicable
Web Search$0 / 1M——
Request——$0.0336 / request
Billing——Pay Per Request
Context
Max context1M—N/A
Max outputN/A—N/A
Capabilities
VisionYes—Yes
Function CallingYes—No
JSON ModeYes—No
StreamingYes—No
Catalogue
ProviderMeta—Google
Categorychat—image
Charge typePay As You Go—Pay Per Request
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.—Gemini 3.1 Flash Lite Image served from Google AI Studio. Billed per image at US$0.0336. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 1K. A request for a larger size returns a 1K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size.