Google's most intelligent Flash model — long-horizon coding, autonomous agents, and multimodal reasoning at Flash-tier pricing.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3-8-flash",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Overview
Gemini 3.8 Flash is Google DeepMind's most capable Flash-tier model, released September 2, 2026 as an iteration on Gemini 3.7 Flash. It targets long-horizon software engineering, autonomous agents, and multi-step reasoning, with a 1M-token context window, multimodal input, and tunable thinking levels.
On Venice, Gemini 3.8 Flash runs under the anonymized privacy tier: your prompts are not stored, profiled, or used for training — a meaningful difference from sending the same queries through a Big-Tech console tied to your identity. Access is permissionless: pay per token, no subscription, and the same model is reachable through the Venice API. Note that Venice's zero-retention handling applies to your prompts; the model itself remains Google's closed, safety-filtered weights.
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-3-8-flash",
"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-3-8-flash",
"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-3-8-flash",
messages=[{"role": "user", "content": "Build without permission."}],
)
print(resp.choices[0].message.content)Specifications
Assessment
Use cases
Prompting
Set the thinking level explicitly: 'low' for quick extraction and drafting, 'high' for hard multi-step reasoning — 'medium' is the default.
Feed PDFs, screenshots, audio, or video directly as input instead of transcribing them first; the model ingests all of them natively.
Request a JSON schema when you need machine-readable output — structured output is supported and keeps agent pipelines deterministic.
Use the 1M-token window to paste whole codebases or document sets rather than chunking; long-context retrieval is a core design target.
Ask the model to search the web for current facts instead of relying on training data — search grounding is built in.
For repeated prompts with large shared prefixes (system prompts, docs), cached input on Venice costs $0.09 per 1M tokens — structure prompts to exploit it.
Alternatives
| Model | Best for | Context | Open weights | Price (Venice) |
|---|---|---|---|---|
| Gemini 3.8 Flash | Long-horizon coding & agents | 1M tokens | No | $0.94 in · $4.69 out / 1M |
| Claude Sonnet 4.6 | Balanced quality & reliability | 1M tokens | No | $3.60 in · $18 out / 1M |
| Qwen 3.7 Plus | High-volume on a budget | 1M tokens | No | $0.50 in · $2 out / 1M |
| Kimi K3 | Open-weight frontier work | 1M tokens | Yes | $3.75 in · $18.75 out / 1M |
| Grok 4.7 | Reasoning with real-time pull | 500K tokens | No | $2.27 in · $6.80 out / 1M |
Gemini 3.8 Flash is the right pick for long-horizon coding and autonomous agent work where you want near-frontier reasoning without paying frontier prices — and it's the cheapest multimodal 1M-context option on Venice that accepts video and audio input.
Pricing
Billed per token on Venice: $0.94 per 1M input tokens and $4.69 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-3-8-flash as the model and send the request.
FAQ
Gemini 3.8 Flash is Google DeepMind's most intelligent Flash-tier model, released September 2, 2026. Built on Gemini 3.7 Flash, it targets long-horizon software engineering, autonomous agents, and complex multi-step reasoning, with a 1M-token context window, 64K max output, and multimodal input covering text, images, video, audio, and PDFs.
On Venice, Gemini 3.8 Flash is billed per token: $0.94 per 1M input tokens, $4.69 per 1M output tokens, and $0.09 per 1M cached input tokens. There is no subscription required — you pay only for what you use. Google's own list pricing differs, so Venice's rates are the ones that apply here.
Gemini 3.8 Flash is neither free-software nor open-source: it is a proprietary Google model with closed weights, so it cannot be self-hosted or fine-tuned. It is not free to run, though Venice offers free daily prompts and welcome credits for trying it. If you need open weights, Kimi K3 or Google Gemma 4 31B Instruct are the closest alternatives on Venice.
Yes. Gemini 3.8 Flash supports function calling, structured output via JSON schema, search grounding (web search), and URL context, making it well suited to agentic pipelines. On Venice you can combine these with the anonymized privacy tier so your agent traffic is not stored or profiled.
Yes. Gemini 3.8 Flash accepts text, images, video, audio, and PDF documents as input and produces text output. It does not generate images or audio — for image generation you would use a dedicated image model on Venice.
Both offer 1M-token contexts, but Gemini 3.8 Flash costs $0.94/$4.69 per 1M tokens on Venice versus $3.60/$18 for Claude Sonnet 4.6, and adds native video and audio input. Sonnet 4.6 remains a strong general-purpose choice with a different output style. For cost-sensitive agentic and coding workloads, Gemini 3.8 Flash is the better value; pick Sonnet if you prefer Anthropic's behavior on your tasks.
Venice runs it under the anonymized privacy tier: prompts are not stored, tied to your identity, or used for training. This is not the same as end-to-end encryption or TEE-based local processing — the inference happens on Venice's infrastructure, but your conversation content is not retained.
Gemini 3.8 Flash supports tunable thinking at low, medium, and high levels, with medium as the default. The 'minimal' level from earlier Gemini models is not supported and returns an error. Lower levels trade reasoning depth for speed and cost.
Google released Gemini 3.8 Flash on September 2, 2026, alongside its security-focused sibling Gemini 3.8 Flash Cyber. It has been available on Venice since September 2026.
One key, free to start, no credit card.