Google DeepMind's strongest reasoning model — built for long-horizon agentic coding, cybersecurity defense, and scientific research on a 1M-token context.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-4-carbon",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Overview
Gemini 4 Carbon is Google DeepMind's strongest frontier reasoning model, released on November 10, 2026 and built on Gemini 4 Argon. It targets long-horizon agentic workflows — multi-step coding, cybersecurity defense, and scientific research — with a 1M-token context window, vision, audio and video input, tool use, web search, and tunable thinking levels.
On Venice, Gemini 4 Carbon runs under the anonymized privacy tier: your prompts are not stored, profiled, or fed into a training pipeline, and nothing ties your sessions to a personal advertising profile. That is anonymized handling rather than end-to-end encryption — Venice reserves TEE-isolated routing for other tiers — but it is still a far stricter default than Google's own AI Studio, which logs and retains your conversations. You pay per token with no subscription and no Gemini account.
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-carbon",
"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-carbon",
"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-carbon",
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 quick drafts, high for architecture reviews or security audits where verification loops pay for themselves.
Dump the whole codebase or document set into the 1M-token context instead of summarizing — Carbon reasons best over complete material.
Ask for structured output with an explicit JSON schema when feeding results into another agent or script.
Pair function calling with a verification step: have the model call your tests or linters and iterate on failures before answering.
Use web search grounding for questions with post-training developments, and ask it to cite what it found.
Put your stable system prompt and reference docs up front and reuse them — Venice bills cached input at $0.13 per 1M tokens versus $2.50 fresh.
Alternatives
| Model | Best for | Context | Open weights | Price (Venice) |
|---|---|---|---|---|
| Gemini 4 Carbon | Long-horizon agentic coding & security | 1M tokens | No | $2.50 in · $12.50 out / 1M |
| Gemini 3.8 Flash | Fast everyday knowledge work | 1M tokens | No | $0.94 in · $4.69 out / 1M |
| Grok 4.7 | Real-time search & value | 500K tokens | No | $2.27 in · $6.80 out / 1M |
| Qwen 3.8 Max | Balanced frontier work | 1M tokens | No | $2.50 in · $7.50 out / 1M |
| Muse Spark Open | Open-weights 1M-context work | 1M tokens | Yes | $1.56 in · $5.31 out / 1M |
Pick Gemini 4 Carbon when the problem is genuinely hard — multi-step debugging, security review, or research that rewards deep verification — and accept the slower, token-heavy responses. For routine work at a third of the price, Gemini 3.8 Flash is the better daily driver.
Pricing
Billed per token on Venice: $2.50 per 1M input tokens and $12.50 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-carbon as the model and send the request.
FAQ
Gemini 4 Carbon is Google DeepMind's strongest frontier reasoning model, released November 10, 2026 and built on Gemini 4 Argon. It is designed for long-horizon agentic workflows — complex multi-step coding, cybersecurity defense, and scientific reasoning — with a 1M-token context window and tunable thinking levels.
Venice bills Gemini 4 Carbon per token: $2.50 per 1M input tokens, $12.50 per 1M output tokens, and $0.13 per 1M cached input tokens. There is no subscription required — you pay only for what you use.
No. Gemini 4 Carbon is closed and proprietary to Google — the weights are not public and it cannot be self-hosted or fine-tuned. If you need open weights on Venice, Muse Spark Open or Google Gemma 4 31B Instruct are the closest alternatives.
Gemini 4 Carbon is for the hardest tasks: long agent runs, multi-step debugging, and deep research where it spends extra thinking tokens verifying its work. Gemini 3.8 Flash is faster and roughly a third of the price on Venice, which makes it the better default for everyday prompts. Use Carbon when Flash's answers keep falling short.
Yes. On Venice, Gemini 4 Carbon supports function calling, structured JSON-schema output, and web search grounding, alongside vision, audio, and video input. That combination is what makes it suited to sustained agentic workflows rather than single-shot chat.
Venice runs Gemini 4 Carbon under its anonymized privacy tier: prompts are not stored, profiled, or used for training, and your usage is not tied to a personal advertising profile. You can use it in the Venice app or through the Venice API. Note this is anonymized handling, not end-to-end encrypted TEE isolation.
Gemini 4 Carbon has a unified 1M-token context window covering text, images, audio, and video combined, with up to 64K tokens of output per response on Venice.
No — Gemini 4 Carbon ships with Google's standard safety alignment, and Venice does not strip it. If you need an uncensored model, Venice Uncensored 1.2 is the purpose-built option on the platform, at a much lower price and a smaller 128K context.
One key, free to start, no credit card.