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

4 is the maximum. Remove one to add another.

gemini-4-hydrogen vs s1 vs nemotron-3.5-super-vl vs gemini-4-carbon
AttributeGemini 4 Hydrogengemini-4-hydrogenS1s1Nemotron 3.5 Super VLnemotron-3.5-super-vlGemini 4 Carbongemini-4-carbon
Pricing
Input$1.50 / 1M— Not priced per input token$0.10 / 1M$2.00 / 1M
Output$7.50 / 1M— Not priced per output token$0.40 / 1M$10.00 / 1M
Cache Write (5m)$1.50 / 1MNot applicable$0.10 / 1M$2.00 / 1M
Cache Write (1h)$1.50 / 1MNot applicable$0.10 / 1M$2.00 / 1M
Cache Read$1.50 / 1MNot applicable$0.10 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1MN/A1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderGoogleFish AudioNVIDIAGoogle
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay 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.Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.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 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.