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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. Gemini 3.1 Flash Lite Image (Google Vertex AI)GoogleRemove
  2. mai-ds-r1:freeNot in the catalogueRemove
  3. Muse WonderMetaRemove
gemini-3.1-flash-lite-image-vertex vs mai-ds-r1:free vs muse-wonder
AttributeGemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexmai-ds-r1:freeNot in the catalogueMuse Wondermuse-wonder
Pricing
Request$0.0336 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable—$4.00 / 1M
Cache Write (1h)Not applicable—$4.00 / 1M
Cache ReadNot applicable—$4.00 / 1M
Input——$4.00 / 1M
Output——$20.00 / 1M
Web Search——$0 / 1M
Context
Max contextN/A—1M
Max outputN/A—N/A
Capabilities
VisionYes—Yes
Function CallingNo—Yes
JSON ModeNo—Yes
StreamingNo—Yes
Catalogue
ProviderGoogle—Meta
Categoryimage—chat
Charge typePay Per Request—Pay As You Go
Released———
Description
SummaryGemini 3.1 Flash Lite Image served from Google Vertex AI. 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.—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.