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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 Spark OpenMetaRemove
  2. Voxtral Small 24B 2507Mistral AIRemove
  3. Nemotron 3.5 Super VL (Free)NVIDIARemove
muse-spark-open vs voxtral-small-24b-2507 vs nemotron-3.5-super-vl:free
AttributeMuse Spark Openmuse-spark-openVoxtral Small 24B 2507voxtral-small-24b-2507Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free
Pricing
Input$1.25 / 1M$0.125 / 1M$0 / 1M
Output$4.25 / 1M$0.375 / 1M$0 / 1M
Cache Write (5m)$1.25 / 1MNot applicable—
Cache Write (1h)$1.25 / 1MNot applicable—
Cache Read$1.25 / 1MNot applicable$0 / 1M
Web Search$0 / 1M$0 / 1M—
Cache Write——$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 GoFree
Released———
Description
SummaryMuse 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.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.