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 | Kimi K3.1 Prokimi-k3.1-pro | Muse Wondermuse-wonder | GPT Transcribegpt-transcribe |
|---|---|---|---|
| Pricing | |||
| Input | $2.00 / 1M | $4.00 / 1M | — Not priced per input token |
| Output | $10.00 / 1M | $20.00 / 1M | — Not priced per output token |
| Cache Write (5m) | $2.00 / 1M | $4.00 / 1M | Not applicable |
| Cache Write (1h) | $2.00 / 1M | $4.00 / 1M | Not applicable |
| Cache Read | $2.00 / 1M | $4.00 / 1M | Not applicable |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1M | 1M | N/A |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | No |
| Function Calling | Yes | Yes | No |
| JSON Mode | Yes | Yes | No |
| Streaming | Yes | Yes | No |
| Catalogue | |||
| Provider | MoonShot AI | Meta | OpenAI |
| Category | chat | chat | voice |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | 2026-08-05 |
| Description | |||
| Summary | Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution. | 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. | OpenAI GPT Transcribe speech-to-text. Billed per second of audio. |