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.
- Muse WonderMetaRemove
- Gemini 4 ArgonGoogleRemove
- GPT TranscribeOpenAIRemove
- Nemotron 3.5 Super VL (Free)NVIDIARemove
4 is the maximum. Remove one to add another.
| Attribute | Muse Wondermuse-wonder | Gemini 4 Argongemini-4-argon | GPT Transcribegpt-transcribe | Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free |
|---|---|---|---|---|
| Pricing | ||||
| Input | $4.00 / 1M | $2.00 / 1M | — Not priced per input token | $0 / 1M |
| Output | $20.00 / 1M | $10.00 / 1M | — Not priced per output token | $0 / 1M |
| Cache Write (5m) | $4.00 / 1M | $2.00 / 1M | Not applicable | — |
| Cache Write (1h) | $4.00 / 1M | $2.00 / 1M | Not applicable | — |
| Cache Read | $4.00 / 1M | $2.00 / 1M | Not applicable | $0 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | — |
| Cache Write | — | — | — | $0 / 1M |
| Context | ||||
| Max context | 1M | 1M | N/A | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | Yes | No | Yes |
| Function Calling | Yes | Yes | No | Yes |
| JSON Mode | Yes | Yes | No | Yes |
| Streaming | Yes | Yes | No | Yes |
| Catalogue | ||||
| Provider | Meta | OpenAI | NVIDIA | |
| Category | chat | chat | voice | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Free |
| Released | — | — | 2026-08-05 | — |
| 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 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response. | OpenAI GPT Transcribe speech-to-text. Billed per second of audio. | NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications. |