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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. GPT-6 Luna ProOpenAIRemove
  2. Muse WonderMetaRemove
  3. Qwen3.8 27BAlibabaRemove
  4. Gemini 3.8 FlashGoogleRemove

4 is the maximum. Remove one to add another.

gpt-6-luna-pro vs muse-wonder vs qwen3.8-27b vs gemini-3.8-flash
AttributeGPT-6 Luna Progpt-6-luna-proMuse Wondermuse-wonderQwen3.8 27Bqwen3.8-27bGemini 3.8 Flashgemini-3.8-flash
Pricing
Input$0.10 / 1M$4.00 / 1M$0.45 / 1M$0.75 / 1M
Output$0.50 / 1M$20.00 / 1M$3.20 / 1M$3.75 / 1M
Cache Write (5m)$0.10 / 1M$4.00 / 1M$0.45 / 1M$0.75 / 1M
Cache Write (1h)$0.10 / 1M$4.00 / 1M$0.45 / 1M$0.75 / 1M
Cache Read$0.10 / 1M$4.00 / 1M$0.45 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1M1M262K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAIMetaAlibabaGoogle
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
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.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 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.