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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 3.5 Lightning (Free)NVIDIARemove
  2. DeepSeek V4.1 FlashDeepSeekRemove
  3. GPT-6 LunaOpenAIRemove
nemotron-3.5-lightning:free vs deepseek-v4.1-flash vs gpt-6-luna
AttributeNemotron 3.5 Lightning (Free)nemotron-3.5-lightning:freeDeepSeek V4.1 Flashdeepseek-v4.1-flashGPT-6 Lunagpt-6-luna
Pricing
Input$0 / 1M$0.30 / 1M$0.10 / 1M
Output$0 / 1M$1.20 / 1M$0.50 / 1M
Cache Write$0 / 1M——
Cache Read$0 / 1M$0.30 / 1M$0.10 / 1M
Cache Write (5m)—$0.30 / 1M$0.10 / 1M
Cache Write (1h)—$0.30 / 1M$0.10 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context1M1M1.1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderNVIDIADeepSeekOpenAI
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.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.