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.
- Gemini 3.5 TranscribeGoogleRemove
- Muse WonderMetaRemove
- GLM 5.3 FlashZ.AIRemove
- Muse Spark OpenMetaRemove
4 is the maximum. Remove one to add another.
| Attribute | Gemini 3.5 Transcribegemini-3.5-transcribe | Muse Wondermuse-wonder | GLM 5.3 Flashglm-5.3-flash | Muse Spark Openmuse-spark-open |
|---|---|---|---|---|
| Pricing | ||||
| Input | — Not priced per input token | $4.00 / 1M | $0.075 / 1M | $1.25 / 1M |
| Output | — Not priced per output token | $20.00 / 1M | $0.25 / 1M | $4.25 / 1M |
| Cache Write (5m) | Not applicable | $4.00 / 1M | $0.075 / 1M | $1.25 / 1M |
| Cache Write (1h) | Not applicable | $4.00 / 1M | $0.075 / 1M | $1.25 / 1M |
| Cache Read | Not applicable | $4.00 / 1M | $0.075 / 1M | $1.25 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 98.3K | 1M | 1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes | Yes |
| Streaming | No | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Meta | Z.AI | Meta | |
| Category | voice | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | 2026-09-25 | — | — | — |
| Description | ||||
| Summary | Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token. | 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. | GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads. | Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential. |