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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. S1Fish AudioRemove
gemini-4-hydrogen vs nemotron-3.5-super-vl:free vs s1
AttributeGemini 4 Hydrogengemini-4-hydrogenNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeS1s1
Pricing
Input$1.50 / 1M$0 / 1M— Not priced per input token
Output$7.50 / 1M$0 / 1M— Not priced per output token
Cache Write (5m)$1.50 / 1M—Not applicable
Cache Write (1h)$1.50 / 1M—Not applicable
Cache Read$1.50 / 1M$0 / 1MNot applicable
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max context1M1MN/A
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderGoogleNVIDIAFish Audio
Categorychatchatvoice
Charge typePay As You GoFreePay 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.Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.