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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. Universal-3.5 ProAssemblyAIRemove
  2. Nemotron 3.5 LightningNVIDIARemove
  3. Gemini 4 ArgonGoogleRemove
universal-3-5-pro vs nemotron-3.5-lightning vs gemini-4-argon
AttributeUniversal-3.5 Prouniversal-3-5-proNemotron 3.5 Lightningnemotron-3.5-lightningGemini 4 Argongemini-4-argon
Pricing
Input— Not priced per input token— Not priced per input token$2.00 / 1M
Output— Not priced per output token— Not priced per output token$10.00 / 1M
Cache Write (5m)Not applicable$0.00 / 1M$2.00 / 1M
Cache Write (1h)Not applicable$0.00 / 1M$2.00 / 1M
Cache ReadNot applicable$0.00 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderAssemblyAINVIDIAGoogle
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-22——
Description
SummaryAssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio.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.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.