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.
| Attribute | Transcribe 1 Protranscribe-1-pro | Muse Wondermuse-wonder | mai-ds-r1:freeNot in the catalogue |
|---|---|---|---|
| Pricing | |||
| Input | — Not priced per input token | $4.00 / 1M | — |
| Output | — Not priced per output token | $20.00 / 1M | — |
| Cache Write (5m) | Not applicable | $4.00 / 1M | — |
| Cache Write (1h) | Not applicable | $4.00 / 1M | — |
| Cache Read | Not applicable | $4.00 / 1M | — |
| Web Search | $0 / 1M | $0 / 1M | — |
| Context | |||
| Max context | N/A | 1M | — |
| Max output | N/A | N/A | — |
| Capabilities | |||
| Vision | No | Yes | — |
| Function Calling | No | Yes | — |
| JSON Mode | No | Yes | — |
| Streaming | No | Yes | — |
| Catalogue | |||
| Provider | Fish Audio | Meta | — |
| Category | voice | chat | — |
| Charge type | Pay As You Go | Pay As You Go | — |
| Released | 2026-09-24 | — | — |
| Description | |||
| Summary | Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio. | 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. | — |