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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 Nano Omni (Free)NVIDIARemove
  2. Gemini 4 ArgonGoogleRemove
nemotron-3-nano-omni-30b-a3b-reasoning:free vs gemini-4-argon
AttributeNemotron 3 Nano Omni (Free)nemotron-3-nano-omni-30b-a3b-reasoning:freeGemini 4 Argongemini-4-argon
Pricing
Input$0 / 1M$2.00 / 1M
Output$0 / 1M$10.00 / 1M
Cache Write$0 / 1M—
Cache Read$0 / 1M$2.00 / 1M
Cache Write (5m)—$2.00 / 1M
Cache Write (1h)—$2.00 / 1M
Web Search—$0 / 1M
Context
Max context256K1M
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderNVIDIAGoogle
Categorychatchat
Charge typeFreePay As You Go
Released——
Description
SummaryNVIDIA Nemotron 3 Nano Omni is an open 30B-A3B multimodal model designed as a perception and context sub-agent for enterprise agent systems. It supports text, image, video, and audio inputs with text output, enabling unified multimodal reasoning within a single inference loop. Built on a hybrid MoE Transformer–Mamba architecture with Conv3D video layers and Efficient Video Sampling (EVS), it delivers significantly improved efficiency for video reasoning—achieving ~2× higher throughput and 2.5× lower compute compared to separate pipelines. With up to 300K context length and extended thinking support, it is well suited for scalable, multimodal agent workflows.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.