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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. Nemotron 3.5 LightningNVIDIARemove
  3. Perceptron Mk1.5PerceptronRemove
muse-spark-open vs nemotron-3.5-lightning vs perceptron-mk1.5
AttributeMuse Spark Openmuse-spark-openNemotron 3.5 Lightningnemotron-3.5-lightningPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$1.25 / 1M— Not priced per input token$0.15 / 1M
Output$4.25 / 1M— Not priced per output token$1.50 / 1M
Cache Write (5m)$1.25 / 1M$0.00 / 1M$0.15 / 1M
Cache Write (1h)$1.25 / 1M$0.00 / 1M$0.15 / 1M
Cache Read$1.25 / 1M$0.00 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderMetaNVIDIAPerceptron
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released——2026-09-25
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.NVIDIA Nemotron 3.5 Lightning is an open Mixture-of-Experts (MoE) model with 30B total parameters and 3B active per token, optimized for high-throughput agentic workloads and efficient inference. Its lightweight active compute and open design make it well suited for specialized agents, domain-specific customization, and scalable production deployments where speed, cost efficiency, and adaptability are key.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.