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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.

  1. Muse WonderMetaRemove
  2. Voxtral Small 24B 2507Mistral AIRemove
  3. Nemotron 3.5 Super VLNVIDIARemove
muse-wonder vs voxtral-small-24b-2507 vs nemotron-3.5-super-vl
AttributeMuse Wondermuse-wonderVoxtral Small 24B 2507voxtral-small-24b-2507Nemotron 3.5 Super VLnemotron-3.5-super-vl
Pricing
Input$4.00 / 1M$0.125 / 1M$0.10 / 1M
Output$20.00 / 1M$0.375 / 1M$0.40 / 1M
Cache Write (5m)$4.00 / 1MNot applicable$0.10 / 1M
Cache Write (1h)$4.00 / 1MNot applicable$0.10 / 1M
Cache Read$4.00 / 1MNot applicable$0.10 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M32K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesYesYes
Catalogue
ProviderMetaMistral AINVIDIA
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryMuse 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.Voxtral Small is an upgraded version of Mistral Small 3 that adds advanced audio understanding while preserving strong text performance. It handles speech transcription, translation, and audio comprehension, with audio input billed per million seconds.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.