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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. Nemotron 3.5 Lightning (Free)NVIDIARemove
  2. Muse Spark 1.3MetaRemove
  3. GPT-6 SolOpenAIRemove
nemotron-3.5-lightning:free vs muse-spark-1.3 vs gpt-6-sol
AttributeNemotron 3.5 Lightning (Free)nemotron-3.5-lightning:freeMuse Spark 1.3muse-spark-1.3GPT-6 Solgpt-6-sol
Pricing
Input$0 / 1M$1.25 / 1M$2.00 / 1M
Output$0 / 1M$4.25 / 1M$10.00 / 1M
Cache Write$0 / 1M——
Cache Read$0 / 1M$1.25 / 1M$2.00 / 1M
Cache Write (5m)—$1.25 / 1M$2.00 / 1M
Cache Write (1h)—$1.25 / 1M$2.00 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context1M1M1.1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderNVIDIAMetaOpenAI
Categorychatchatchat
Charge typeFreePay As You GoPay As You Go
Released———
Description
SummaryNVIDIA 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.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.GPT-6 Sol is OpenAI's cost-efficient high-end model in the GPT-6 series, positioned between the flagship GPT-6 Astra and the fast GPT-6 Luna tier. It is designed for professional knowledge work, agentic coding, business workflow automation, and computer-use tasks, with particular strength in long-horizon software engineering across real-world codebases. GPT-6 Sol approaches Astra-level factual reliability at a significantly lower cost, while sharing its clear and concise communication style. This balance of capability, reliability, and efficiency makes it well suited for production agents, complex engineering workflows, and scalable professional applications