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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. Muse WonderMetaRemove
  2. GPT-4o Mini TranscribeOpenAIRemove
muse-wonder vs gpt-4o-mini-transcribe
AttributeMuse Wondermuse-wonderGPT-4o Mini Transcribegpt-4o-mini-transcribe
Pricing
Input$4.00 / 1M$0.625 / 1M
Output$20.00 / 1M$0.625 / 1M
Cache Write (5m)$4.00 / 1MNot applicable
Cache Write (1h)$4.00 / 1MNot applicable
Cache Read$4.00 / 1MNot applicable
Web Search$0 / 1M$0 / 1M
Context
Max context1M128K
Max outputN/AN/A
Capabilities
VisionYesNo
Function CallingYesNo
JSON ModeYesYes
StreamingYesNo
Catalogue
ProviderMetaOpenAI
Categorychatvoice
Charge typePay As You GoPay As You Go
Released——
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.GPT-4o Mini Transcribe is a smaller, cost-efficient speech-to-text model built on GPT-4o Mini's audio capabilities. It is designed for high-volume transcription workloads, delivering reliable performance with lower cost and latency. Priced per token (input and output), it provides transparent, fine-grained billing, making it well suited for scalable transcription pipelines, real-time applications, and cost-sensitive deployments.