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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. Nemotron 3.5 Super VLNVIDIARemove
  2. Gemini 4 ArgonGoogleRemove
  3. S1Fish AudioRemove
  4. Gemini 4 CarbonGoogleRemove

4 is the maximum. Remove one to add another.

nemotron-3.5-super-vl vs gemini-4-argon vs s1 vs gemini-4-carbon
AttributeNemotron 3.5 Super VLnemotron-3.5-super-vlGemini 4 Argongemini-4-argonS1s1Gemini 4 Carbongemini-4-carbon
Pricing
Input$0.10 / 1M$2.00 / 1M— Not priced per input token$2.00 / 1M
Output$0.40 / 1M$10.00 / 1M— Not priced per output token$10.00 / 1M
Cache Write (5m)$0.10 / 1M$2.00 / 1MNot applicable$2.00 / 1M
Cache Write (1h)$0.10 / 1M$2.00 / 1MNot applicable$2.00 / 1M
Cache Read$0.10 / 1M$2.00 / 1MNot applicable$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1MN/A1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderNVIDIAGoogleFish AudioGoogle
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-07-29—
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.Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.Gemini 4 Carbon is Google's frontier multimodal reasoning model, designed for advanced coding, agentic workflows, and complex multi-step problem solving. It supports text, image, audio, video, and file inputs, enabling integrated reasoning and analysis across diverse modalities. Optimized for long-horizon execution and demanding professional workloads, Gemini 4 Carbon supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high) to balance reasoning depth, latency, and cost. It is well suited for autonomous agents, software engineering, multimodal analysis, and large-scale workflow automation.