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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. Nemotron 3 UltraNVIDIARemove
  2. Muse WonderMetaRemove
  3. Muse Spark OpenMetaRemove
nemotron-3-ultra-550b-a55b vs muse-wonder vs muse-spark-open
AttributeNemotron 3 Ultranemotron-3-ultra-550b-a55bMuse Wondermuse-wonderMuse Spark Openmuse-spark-open
Pricing
Input$0.50 / 1M$4.00 / 1M$1.25 / 1M
Output$2.50 / 1M$20.00 / 1M$4.25 / 1M
Cache Write (5m)$0.50 / 1M$4.00 / 1M$1.25 / 1M
Cache Write (1h)$0.50 / 1M$4.00 / 1M$1.25 / 1M
Cache Read$0.50 / 1M$4.00 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderNVIDIAMetaMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryNVIDIA Nemotron 3 Ultra is an open frontier reasoning and orchestration model featuring a 550B-parameter Mixture-of-Experts (MoE) architecture with 55B active parameters per token. Built on a hybrid Transformer–Mamba design, it supports text input and output with a 1M-token context window, enabling large-scale reasoning and long-horizon task execution. Optimized for agent orchestration, coding agents, deep research, and complex enterprise workflows, the model excels at multi-step reasoning, planning, and sustained execution. With high-throughput inference designed for large-scale agent pipelines, Nemotron 3 Ultra serves as a powerful foundation for advanced agentic AI systems.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.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.