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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 Super VL (Free)NVIDIARemove
  2. Gemini 4 ArgonGoogleRemove
  3. Gemini 2.5 Flash Image (Nano Banana)GoogleRemove
nemotron-3.5-super-vl:free vs gemini-4-argon vs gemini-2.5-flash-image
AttributeNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGemini 4 Argongemini-4-argonGemini 2.5 Flash Image (Nano Banana)gemini-2.5-flash-image
Pricing
Input$0 / 1M$2.00 / 1M$0.30 / 1M
Output$0 / 1M$10.00 / 1M$2.50 / 1M
Cache Write$0 / 1M——
Cache Read$0 / 1M$2.00 / 1MNot applicable
Cache Write (5m)—$2.00 / 1MNot applicable
Cache Write (1h)—$2.00 / 1MNot applicable
Web Search—$0 / 1M$0 / 1M
Context
Max context1M1MN/A
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderNVIDIAGoogleGoogle
Categorychatchatimage
Charge typeFreePay As You GoPay As You Go
Released———
Description
SummaryNVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.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.Gemini 2.5 Flash Image (“Nano Banana”) is now generally available. It’s a state-of-the-art image generation model with strong contextual understanding, supporting image creation, editing, and multi-turn conversational workflows around visuals.