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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 AstraOpenAIRemove
nemotron-3.5-lightning:free vs muse-spark-1.3 vs gpt-6-astra
AttributeNemotron 3.5 Lightning (Free)nemotron-3.5-lightning:freeMuse Spark 1.3muse-spark-1.3GPT-6 Astragpt-6-astra
Pricing
Input$0 / 1M$1.25 / 1M$10.00 / 1M
Output$0 / 1M$4.25 / 1M$50.00 / 1M
Cache Write$0 / 1M
Cache Read$0 / 1M$1.25 / 1M$10.00 / 1M
Cache Write (5m)$1.25 / 1M$10.00 / 1M
Cache Write (1h)$1.25 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M1M1M
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 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.