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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. Gemini 4 HydrogenGoogleRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. Gemini 4 ArgonGoogleRemove
  4. S1Fish AudioRemove

4 is the maximum. Remove one to add another.

gemini-4-hydrogen vs nemotron-3.5-super-vl:free vs gemini-4-argon vs s1
AttributeGemini 4 Hydrogengemini-4-hydrogenNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGemini 4 Argongemini-4-argonS1s1
Pricing
Input$1.50 / 1M$0 / 1M$2.00 / 1M— Not priced per input token
Output$7.50 / 1M$0 / 1M$10.00 / 1M— Not priced per output token
Cache Write (5m)$1.50 / 1M—$2.00 / 1MNot applicable
Cache Write (1h)$1.50 / 1M—$2.00 / 1MNot applicable
Cache Read$1.50 / 1M$0 / 1M$2.00 / 1MNot applicable
Web Search$0 / 1M—$0 / 1M$0 / 1M
Cache Write—$0 / 1M——
Context
Max context1M1M1MN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderGoogleNVIDIAGoogleFish Audio
Categorychatchatchatvoice
Charge typePay As You GoFreePay As You GoPay As You Go
Released———2026-07-29
Description
SummaryGemini 4 Hydrogen is Google's high-efficiency multimodal model in the Gemini 4 family, optimized for high-throughput agentic workflows, coding, and multi-model routing. It delivers strong performance at lower cost and latency than Gemini 4 Carbon, supporting text, image, audio, video, and file inputs for versatile multimodal applications. Designed for scalable production workloads and long-horizon execution, Gemini 4 Hydrogen supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high, and xhigh) to balance reasoning depth, speed, and cost. It is well suited for coding assistants, autonomous agents, complex workflow automation, and large-scale AI systems.NVIDIA 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.