Gemini 3.5 Flash
Google's fast, agent-first multimodal model, delivering frontier-level reasoning and coding at Flash speeds.
Overview
What is Gemini 3.5 Flash
Gemini 3.5 Flash is Google's highly efficient, natively multimodal model released in May 2026. Optimized for the agentic era, it delivers frontier-level reasoning, coding, and tool use at high speeds, outperforming previous Pro-tier models on complex multi-step workflows while maintaining low latency.
Running it privately on Venice
On Venice, you can access Gemini 3.5 Flash's massive 1M token context window and multimodal capabilities under our anonymized privacy tier. While hosted by a third-party provider, Venice forwards requests anonymously to prevent personal profiling. This allows you to deploy advanced agentic workflows and analyze sensitive documents without tying your data to a persistent Big-Tech identity.
Assessment
Strengths and limitations
- Exceptional agentic performance: leads on MCP Atlas tool-use (83.6%) and excels at multi-step sub-agent orchestration.
- Blazing fast speeds: runs up to 4x faster than comparable frontier models like Claude Opus 4.7.
- Native multimodal inputs: handles text, images, audio, video, and PDFs directly in a single context.
- Massive 1M token context window allows ingestion of entire codebases or long video files.
- Configurable thinking levels to balance reasoning quality, cost, and latency.
- Closed-source and proprietary: lacks open weights, preventing local deployment or private fine-tuning.
- Long-context retrieval degradation: needle-in-a-haystack performance (MRCR v2) drops significantly from 128K to 1M tokens.
- Sub-optimal for complex multi-file software engineering compared to heavyweights like Claude Opus 4.7.
- Not uncensored: subject to Google's strict safety filters and alignment policies.
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
- May 19, 2026
- Architecture
- Gemini 3 Flash foundation
- Modality
- Text, image, audio, video input; text output
- Open weights
- No — proprietary
- Context window
- 1,000K tokens
- Max output
- 65.536K tokens
- Capabilities
- Vision, Function calling, Reasoning, Web search
- Privacy on Venice
- Anonymized — prompts not stored
- Available on Venice since
- May 2026
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-3-5-flash",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $1.55 per 1M input tokens and $9.45 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 | Strongest at | Open weights | Price (Venice) |
|---|---|---|---|---|
| Gemini 3.5 Flash | 1M tokens | Agent orchestration & speed | No | $1.55 in · $9.45 out / 1M |
| Claude Opus 4.7 | 1M tokens | Complex coding & reasoning | No | $6 in · $30 out / 1M |
| DeepSeek V3.2 | 160K tokens | Low-cost open reasoning | Yes | $0.33 in · $0.48 out / 1M |
| Grok 4.3 | 1M tokens | Real-time info & reasoning | No | $1.42 in · $2.83 out / 1M |
The speed and agentic leader in the Flash tier.
Use cases
What it is good for
- 01Orchestration-heavy agent pipelines and rapid multi-step agentic loops.
- 02High-volume document analysis, summarizing long PDFs, or processing audio/video files.
- 03Rapid coding iterations and terminal-based tasks.
- 04Cost-sensitive applications requiring vision, web search, or structured JSON outputs.
Prompting
Getting better results
Provide explicit step-by-step instructions (Chain of Thought) to leverage its strong reasoning capabilities.
Keep critical retrieval facts within the first 128K tokens to avoid long-context retrieval degradation.
Use structured JSON outputs for reliable schema parsing in agentic workflows.
Version history
Initial preview version.
Current stable GA version.
FAQ
Frequently asked questions
Gemini 3.5 Flash is Google's agent-first multimodal model released in May 2026. It is designed to deliver frontier-level reasoning, coding, and tool use at high speeds and low costs, outperforming previous Pro-tier models on complex multi-step workflows.
On Venice, Gemini 3.5 Flash is billed per token at $1.55 per 1M input tokens and $9.45 per 1M output tokens, with cached inputs charged at $0.15 per 1M tokens.
No, Gemini 3.5 Flash is a closed, proprietary model developed by Google DeepMind. However, you can try it on Venice with a free account, which includes daily promotional credits.
Yes. Gemini 3.5 Flash natively supports tool use (function calling), structured JSON output, web search, and multimodal inputs including images, audio, video, and PDFs.
Gemini 3.5 Flash is roughly 4x faster and significantly cheaper, making it ideal for high-volume agent orchestration. Claude Opus 4.7 remains superior for complex, multi-file software engineering tasks.
Venice forwards your requests anonymously to a third-party provider. Your prompts are not stored by Venice, nor are they tied to a personal profile, allowing you to use this frontier model with enhanced privacy.
It features a massive 1M token context window (1,048,576 tokens) for inputs, and supports up to 65,536 tokens for outputs, though retrieval accuracy can degrade at the outer limits of the input window.
Run Gemini 3.5 Flash privately
No prompt logging. No data used for training.