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 | Muse Wondermuse-wonder | Gemini 2.5 Flash Litegemini-2.5-flash-lite |
|---|---|---|
| Pricing | ||
| Input | $4.00 / 1M | $0.15 / 1M |
| Output | $20.00 / 1M | $0.60 / 1M |
| Cache Write (5m) | $4.00 / 1M | $0.15 / 1M |
| Cache Write (1h) | $4.00 / 1M | $0.15 / 1M |
| Cache Read | $4.00 / 1M | $0.15 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 1M | 1.0M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | Meta | |
| Category | chat | chat |
| Charge type | Pay As You Go | Pay As You Go |
| Released | — | — |
| 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. | Gemini 2.5 Flash-Lite is a smaller, low-latency model focused on speed and cost efficiency. It delivers faster generation and better benchmark performance than earlier Flash models. Thinking mode is off by default for maximum speed, but developers can enable it when they want deeper reasoning at a higher cost. |