Gemini 3 Flash Preview
Google's fast, multimodal reasoning model built for agentic coding and high-frequency workflows at a fraction of flagship cost.
Overview
What is Gemini 3 Flash Preview
Gemini 3 Flash Preview is Google's fast, multimodal reasoning model released in December 2025. It handles text, image, video, and audio inputs with tool use and web search, delivering up to 65,536 output tokens. It is designed for high-frequency agentic workflows, coding, and complex document analysis at a fraction of Pro-tier cost.
Running it privately on Venice
On Venice, Gemini 3 Flash Preview runs with zero retention — your prompts are not stored, profiled, or used to refine Google's models. You get the same multimodal speed and reasoning, plus tool use, web search, and structured output, without feeding your data into Big Tech's surveillance pipeline. It is permissionless access to frontier intelligence with sovereignty over your conversations.
Assessment
Strengths and limitations
- Native multimodal inputs: text, image, video, and audio in a single model call.
- Strong reasoning and coding capabilities with support for function calling, web search, and structured output.
- Fast, cost-efficient execution at $0.70/$3.75 per 1M tokens — undercutting many closed rivals.
- Supports reasoning modes that let you balance speed against depth for agentic workflows.
- 256K-token context window and 65,536 max output tokens handle long documents and extended analysis.
- Closed and proprietary: no open weights, so you cannot self-host, audit, or fine-tune it.
- Not uncensored; Google's safety filters remain active and may refuse certain prompts.
- Text-only output: it analyzes images, video, and audio but cannot generate them.
- On Venice the context window is 256K tokens, narrower than the 1M token limit available natively on Google Cloud.
- Third-party reviews cite high hallucination rates on factual tasks; verify critical outputs independently.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- Google DeepMind
- Released
- December 17, 2025
- Modality
- Text, image, video, audio input; text output
- Knowledge cutoff
- January 2025
- Open weights
- No — proprietary
- Context window
- 256K tokens
- Max output
- 65.536K tokens
- Capabilities
- Vision, Function calling, Reasoning, Web search
- Privacy on Venice
- Anonymized — prompts not stored
- Available on Venice since
- Dec 2025
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3-flash-preview",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.70 per 1M input tokens and $3.75 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Context window | Price (Venice) | Open weights | Best for |
|---|---|---|---|---|
| Gemini 3 Flash Preview | 256K tokens | $0.70 in · $3.75 out / 1M | No | Multimodal agents & coding |
| Kimi K2.6 | 256K tokens | $0.75 in · $3.50 out / 1M | Yes | Open long-context reasoning |
| DeepSeek V3.2 | 160K tokens | $0.33 in · $0.48 out / 1M | Yes | Cheap open-weight inference |
| Claude Sonnet 4.6 | 1M tokens | $3.60 in · $18 out / 1M | No | Enterprise accuracy |
The only model in this set with native video and audio input, plus web search and tool use — a closed but capable multimodal workhorse.
Use cases
What it is good for
- 01Agentic coding and software engineering with tool use and reasoning.
- 02Real-time multimodal analysis: video Q&A, document extraction, and visual understanding.
- 03High-frequency interactive applications and responsive chatbots.
- 04Web-grounded research and structured data extraction via JSON schema.
- 05Complex workflow automation that chains function calls and external APIs.
Prompting
Getting better results
Enable reasoning modes to trade latency for depth on complex agentic tasks.
Upload images, video, or audio directly alongside text for native multimodal analysis.
Use structured JSON output schemas to get machine-parseable results from messy inputs.
Cache long inputs when possible — Venice offers cached input at $0.07 per 1M tokens, cutting context costs by 90%.
Version history
Current preview release.
FAQ
Frequently asked questions
Gemini 3 Flash Preview is Google's fast multimodal reasoning model released in December 2025. It processes text, image, video, and audio inputs with tool use, web search, and reasoning, outputting up to 65,536 tokens. It is optimized for agentic coding and high-frequency workflows.
On Venice it costs $0.70 per 1M input tokens and $3.75 per 1M output tokens. Cached input is $0.07 per 1M tokens. You pay per token with no subscription required.
You can access it on Venice using credits; new accounts receive welcome credits to try the model. Ongoing usage is billed per token consumed.
No. It is a proprietary Google model with closed weights. It cannot be self-hosted or fine-tuned outside Google's infrastructure. For open weights, consider DeepSeek V3.2 or Google Gemma 4 on Venice.
Yes. On Venice it supports function calling, web search, structured JSON output, and reasoning, making it suitable for agentic workflows that interact with external tools and APIs.
Choose Gemini 3 Flash Preview for native multimodal inputs (vision, video, audio) and deep tool integration. Choose Kimi K2.6 if you prefer open weights and slightly lower output pricing for long-context reasoning. Both offer 256K context on Venice.
No. Despite its multimodal inputs, it outputs text only. It can analyze images, video, and audio, but cannot generate them.
No. It remains a censored model with Google's safety filters applied. Venice does not store your prompts, but the model itself may refuse certain requests according to its training.
Run Gemini 3 Flash Preview privately
No prompt logging. No data used for training.