Skip to content

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. GPT-6 Luna ProOpenAIRemove
  2. Muse WonderMetaRemove
  3. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
gpt-6-luna-pro vs muse-wonder vs gemini-3.1-flash-image-vertex
AttributeGPT-6 Luna Progpt-6-luna-proMuse Wondermuse-wonderGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertex
Pricing
Input$0.10 / 1M$4.00 / 1M—
Output$0.50 / 1M$20.00 / 1M—
Cache Write (5m)$0.10 / 1M$4.00 / 1MNot applicable
Cache Write (1h)$0.10 / 1M$4.00 / 1MNot applicable
Cache Read$0.10 / 1M$4.00 / 1MNot applicable
Web Search$0 / 1M$0 / 1M—
Request——$0.067 / request
Billing——Pay Per Request
Context
Max context1.1M1MN/A
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderOpenAIMetaGoogle
Categorychatchatimage
Charge typePay As You GoPay As You GoPay Per Request
Released———
Description
SummaryGPT-6 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier.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.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.