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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. Qwen3.8 27BAlibabaRemove
  3. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  4. Perceptron Mk1.5PerceptronRemove

4 is the maximum. Remove one to add another.

muse-wonder vs qwen3.8-27b vs gemini-3.1-flash-image-vertex vs perceptron-mk1.5
AttributeMuse Wondermuse-wonderQwen3.8 27Bqwen3.8-27bGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$4.00 / 1M$0.45 / 1M—$0.15 / 1M
Output$20.00 / 1M$3.20 / 1M—$1.50 / 1M
Cache Write (5m)$4.00 / 1M$0.45 / 1MNot applicable$0.15 / 1M
Cache Write (1h)$4.00 / 1M$0.45 / 1MNot applicable$0.15 / 1M
Cache Read$4.00 / 1M$0.45 / 1MNot applicable$0.15 / 1M
Web Search$0 / 1M$0 / 1M—$0 / 1M
Request——$0.067 / request—
Billing——Pay Per Request—
Context
Max context1M262KN/A36.9K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesNoNo
JSON ModeYesYesNoNo
StreamingYesYesNoYes
Catalogue
ProviderMetaAlibabaGooglePerceptron
Categorychatchatimagechat
Charge typePay As You GoPay As You GoPay Per RequestPay As You Go
Released———2026-09-25
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.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.Gemini 3.1 Flash Image served from Google Vertex AI. Billed per image at US$0.067. 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 2K. A request for a larger size, such as 4K or 4096x4096, returns a 2K 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, for example 4096x4096->2048x2048.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.