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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 WonderMetaRemove
  2. Gemini 3.1 Flash Lite Image (Google Vertex AI)GoogleRemove
  3. Kimi K3.1 ProMoonShot AIRemove
muse-wonder vs gemini-3.1-flash-lite-image-vertex vs kimi-k3.1-pro
AttributeMuse Wondermuse-wonderGemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexKimi K3.1 Prokimi-k3.1-pro
Pricing
Input$4.00 / 1M—$2.00 / 1M
Output$20.00 / 1M—$10.00 / 1M
Cache Write (5m)$4.00 / 1MNot applicable$2.00 / 1M
Cache Write (1h)$4.00 / 1MNot applicable$2.00 / 1M
Cache Read$4.00 / 1MNot applicable$2.00 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.0336 / request—
Billing—Pay Per Request—
Context
Max context1MN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderMetaGoogleMoonShot AI
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay 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.Gemini 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.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.