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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. mai-ds-r1:freeNot in the catalogueRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. GPT-6.1 SolOpenAIRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs gemini-3.8-flash vs gpt-6.1-sol vs muse-wonder
Attributemai-ds-r1:freeNot in the catalogueGemini 3.8 Flashgemini-3.8-flashGPT-6.1 Solgpt-6.1-solMuse Wondermuse-wonder
Pricing
Input—$0.75 / 1M$2.00 / 1M$4.00 / 1M
Output—$3.75 / 1M$10.00 / 1M$20.00 / 1M
Cache Write (5m)—$0.75 / 1M$2.00 / 1M$4.00 / 1M
Cache Write (1h)—$0.75 / 1M$2.00 / 1M$4.00 / 1M
Cache Read—$0.75 / 1M$2.00 / 1M$4.00 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context—1M1M1M
Max output—N/AN/AN/A
Capabilities
Vision—YesYesYes
Function Calling—YesYesYes
JSON Mode—YesYesYes
Streaming—YesYesYes
Catalogue
Provider—GoogleOpenAIMeta
Category—chatchatchat
Charge type—Pay As You GoPay As You GoPay As You Go
Released————
Description
Summary—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.GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.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.