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 | mai-ds-r1:freeNot in the catalogue | Muse Wondermuse-wonder | Transcribe 1 Protranscribe-1-pro |
|---|---|---|---|
| Pricing | |||
| Input | — | $4.00 / 1M | — Not priced per input token |
| Output | — | $20.00 / 1M | — Not priced per output token |
| Cache Write (5m) | — | $4.00 / 1M | Not applicable |
| Cache Write (1h) | — | $4.00 / 1M | Not applicable |
| Cache Read | — | $4.00 / 1M | Not applicable |
| Web Search | — | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | — | 1M | N/A |
| Max output | — | N/A | N/A |
| Capabilities | |||
| Vision | — | Yes | No |
| Function Calling | — | Yes | No |
| JSON Mode | — | Yes | No |
| Streaming | — | Yes | No |
| Catalogue | |||
| Provider | — | Meta | Fish Audio |
| Category | — | chat | voice |
| Charge type | — | Pay As You Go | Pay 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. |