Google DeepMind's fast agentic workhorse — 1M-token context, four thinking levels, native vision, audio and video input, built for everyday coding and agent execution.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-4-hydrogen",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Overview
Gemini 4 Hydrogen is Google DeepMind's fast, efficiency-focused Gemini 4 model, released November 12, 2026 and adapted from Gemini 4 Carbon. It targets everyday coding and agentic workflows with a unified 1M-token context window, four thinking levels, and native vision, audio and video input.
On Venice, Gemini 4 Hydrogen runs under the anonymized privacy tier: your prompts are not stored, profiled, or fed into an advertising profile — a sharp contrast to running it inside a Big-Tech account that ties every query to your identity. You pay per token with credits, no subscription required, and you can call it through the Venice app or the OpenAI-compatible Venice API. Note that Venice's privacy tier anonymizes prompts rather than encrypting them end-to-end in a TEE.
Agent quickstart
The API is OpenAI-compatible: change the base URL and the model id and existing client code works unchanged.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-4-hydrogen",
"stream": true,
"messages": [{ "role": "user", "content": "Draft the release note." }]
}'curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-4-hydrogen",
"messages": [{ "role": "user", "content": "Find the rate limits." }],
"tools": [{
"type": "function",
"function": {
"name": "search_docs",
"description": "Search the API documentation.",
"parameters": {
"type": "object",
"properties": { "query": { "type": "string" } },
"required": ["query"]
}
}
}],
"tool_choice": "auto"
}'import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["VENICE_API_KEY"],
base_url="https://api.venice.ai/api/v1",
)
resp = client.chat.completions.create(
model="gemini-4-hydrogen",
messages=[{"role": "user", "content": "Build without permission."}],
)
print(resp.choices[0].message.content)Specifications
Assessment
Use cases
Prompting
Set the thinking level explicitly: use low for mechanical edits and high or xhigh when the task needs genuine reasoning — the default is high.
Reuse a stable system prompt or document set so Venice's cached input rate ($0.09/1M) kicks in instead of full input pricing.
For very long generations, request background long decode instead of stretching a synchronous call past the 64K output limit.
Ask for a JSON schema up front when you need machine-readable output — the model supports structured output natively.
Feed screenshots, video or audio directly into the same request rather than describing them; the model ingests all three natively.
For agentic coding, describe the verification step you want (run tests, re-read the diff) — the model is tuned to check its own work.
Alternatives
| Model | Best for | Context | Open weights | Price (Venice) |
|---|---|---|---|---|
| Gemini 4 Hydrogen | Fast agentic coding & execution | 1M tokens | No | $1.88 in · $9.38 out / 1M |
| Gemini 3.8 Flash | Cheap high-volume chat & drafting | 1M tokens | No | $0.94 in · $4.69 out / 1M |
| Muse Spark Open | Open-weights work at 1M context | 1M tokens | Yes | $1.56 in · $5.31 out / 1M |
| Qwen 3.8 Max | Frontier reasoning, Alibaba stack | 1M tokens | No | $2.50 in · $7.50 out / 1M |
| Venice Uncensored 1.2 | Unfiltered output on a budget | 128K tokens | Yes | $0.20 in · $0.90 out / 1M |
Gemini 4 Hydrogen is the right pick for fast, disciplined agentic coding and multimodal execution at 1M context — choose Gemini 3.8 Flash to halve the bill on routine work, or Muse Spark Open when open weights are non-negotiable.
Pricing
Billed per token on Venice: $1.88 per 1M input tokens and $9.38 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Getting a key
Create a key in API settings. Nothing else is required to start.
Export it as VENICE_API_KEY so the snippets above run unedited.
Point an existing OpenAI client at https://api.venice.ai/api/v1. The scheme is part of the value: an OpenAI client given a bare host does not resolve it.
Pass gemini-4-hydrogen as the model and send the request.
FAQ
Gemini 4 Hydrogen is Google DeepMind's fast, efficiency-focused Gemini 4 model, released November 12, 2026. Adapted from Gemini 4 Carbon, it is built for everyday coding and agentic workflows, with a unified 1M-token context window, four thinking levels, and native image, audio and video input.
On Venice, Gemini 4 Hydrogen is billed per token at $1.88 per 1M input tokens and $9.38 per 1M output tokens, with cached input at $0.09 per 1M. There is no subscription required — you pay from your credits as you use it.
Gemini 4 Hydrogen is neither free-software nor open-weights: it is proprietary to Google DeepMind and cannot be self-hosted or fine-tuned. Google offers it on a free tier of its own AI Studio, but the weights are closed. On Venice you can try it with welcome credits before paying per token.
Yes. Gemini 4 Hydrogen supports function calling, web search grounding, and structured JSON-schema output, which is exactly why it is positioned for agentic workflows. It also accepts image, audio and video input alongside text in the same request.
Gemini 4 Hydrogen is the official successor and the stronger model on hard coding and agentic sessions, but it costs roughly twice as much per token on Venice. Use Hydrogen for multi-step coding, tool chains and long-context reasoning; use Gemini 3.8 Flash for high-volume, simpler drafting where price dominates.
Venice runs it under the anonymized privacy tier: prompts are not stored, profiled, or used for training, and nothing is tied to a personal account history. This is anonymization rather than end-to-end encryption in a TEE, but it is a fundamentally different posture from using the model inside a Big-Tech account.
Four: low, medium, high (the default) and xhigh. Lower levels respond faster and cheaper for mechanical tasks; xhigh maximizes reasoning depth when a problem genuinely needs it. Output billing includes thinking tokens, so higher levels cost more per request.
Yes. It has a unified 1M-token context window covering input and output, and supports up to 64K synchronous output tokens — extendable to 1M tokens via background long decode. Whole repositories, contract sets, or transcript archives fit in a single request.
No. It ships with Google's standard safety training, so it will refuse some categories of requests. If you need an uncensored model on Venice, Venice Uncensored 1.2 is the purpose-built alternative — with the trade-off of a much smaller context window.
One key, free to start, no credit card.