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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. Muse WonderMetaRemove
  3. Transcribe 1 ProFish AudioRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs muse-wonder vs transcribe-1-pro vs deepseek-v4.1-flash
Attributemai-ds-r1:freeNot in the catalogueMuse Wondermuse-wonderTranscribe 1 Protranscribe-1-proDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input—$4.00 / 1M— Not priced per input token$0.30 / 1M
Output—$20.00 / 1M— Not priced per output token$1.20 / 1M
Cache Write (5m)—$4.00 / 1MNot applicable$0.30 / 1M
Cache Write (1h)—$4.00 / 1MNot applicable$0.30 / 1M
Cache Read—$4.00 / 1MNot applicable$0.30 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context—1MN/A1M
Max output—N/AN/AN/A
Capabilities
Vision—YesNoYes
Function Calling—YesNoYes
JSON Mode—YesNoYes
Streaming—YesNoYes
Catalogue
Provider—MetaFish AudioDeepSeek
Category—chatvoicechat
Charge type—Pay As You GoPay As You GoPay As You Go
Released——2026-09-24—
Description
Summary—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.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.