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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 LightningNVIDIARemove
  2. Gemini 4 ArgonGoogleRemove
  3. GPT-6.1 SolOpenAIRemove
nemotron-3.5-lightning vs gemini-4-argon vs gpt-6.1-sol
AttributeNemotron 3.5 Lightningnemotron-3.5-lightningGemini 4 Argongemini-4-argonGPT-6.1 Solgpt-6.1-sol
Pricing
Input— Not priced per input token$2.00 / 1M$2.00 / 1M
Output— Not priced per output token$10.00 / 1M$10.00 / 1M
Cache Write (5m)$0.00 / 1M$2.00 / 1M$2.00 / 1M
Cache Write (1h)$0.00 / 1M$2.00 / 1M$2.00 / 1M
Cache Read$0.00 / 1M$2.00 / 1M$2.00 / 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
ProviderNVIDIAGoogleOpenAI
Categorychatchatchat
Charge typePay As You GoPay 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.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.