# Gemini 3.5 Flash

Flash-tier intelligence for agentic coding and multi-turn workflows: Gemini 3.5 Flash brings improved parallel execution, sharper instruction following, and richer thinking traces to the Flash line.

- **Model ID:** `google/gemini-3.5-flash`
- **Type:** chat
- **Providers:** google, vertex
- **Context window:** 1,000,000
- **Maximum output tokens:** 64,000
- **Pricing:** $1.5/1M input tokens, $9/1M output tokens
- **Canonical page:** https://vercel.com/ai-gateway/models/gemini-3.5-flash

## Supported parameters

Detailed capability metadata has not been reported for this model.

## Example

```ts
import { streamText } from 'ai'

const result = streamText({
  model: 'google/gemini-3.5-flash',
  prompt: 'Why is the sky blue?'
})
```

## About

Gemini 3.5 Flash is Google's update to the Flash tier, building on Gemini 3 Flash with focused improvements for coding workflows and agentic execution. Coding proficiency and parallel agentic execution loops both improve over previous Flash versions, which makes Gemini 3.5 Flash a better fit for agents that issue concurrent tool calls or refactor code across multiple files in one pass.

Core reasoning, instruction following, and multi-turn coherence all see upgrades. For complex tasks the model produces higher-quality reasoning traces in thinking mode, which is useful when you need to audit the model's intermediate steps or train downstream systems on chain-of-thought data. Gemini 3.5 Flash defaults to the `medium` thinking level, balancing quality against faster, more cost-efficient generation, and exposes `thinkingLevel` and `includeThoughts` through `providerOptions` for finer control.

Because Gemini 3.5 Flash sits at the intersection of agentic capability and Flash-tier throughput, it suits production traffic patterns from low-latency chat interfaces to high-volume code-transformation pipelines. Accessing Gemini 3.5 Flash through AI Gateway adds observability, automatic retries, and provider failover without requiring a Google Cloud account.

## What to consider

Gemini 3.5 Flash defaults to the `medium` thinking level. Set `thinkingLevel` to `'high'` via `providerOptions.google.thinkingConfig` when the task demands deeper reasoning, and enable `includeThoughts` to surface the model's intermediate steps. Parameters like `temperature`, `topP`, `topK`, and `thinking_budget` are not supported.

## When to use

### Best For
- Coding agents that issue parallel tool calls or refactor service code across multiple files in one pass
- Multi-turn assistants where instruction following and conversational coherence drive task completion
- Agentic pipelines that benefit from higher-quality reasoning traces for auditing or debugging
- Cost-sensitive production workloads where the default `medium` thinking level offers a balance between quality and throughput
- Migrations from Gemini 3 Flash where you want the latest coding and agentic improvements without changing tier

### Consider Alternatives When
- Your task requires the deepest reasoning regardless of latency or cost (consider `google/gemini-3-pro-preview` or `google/gemini-3.1-pro-preview`)
- You need native image generation output (consider `google/gemini-3-pro-image` or `google/gemini-3.1-flash-image-preview`)
- Throughput and budget dominate and reasoning depth is not required (consider `google/gemini-3.1-flash-lite-preview`)
- You depend on `temperature`, `topP`, `topK`, or `thinking_budget`, which Gemini 3.5 Flash does not support

## Best for

- **Agentic coding workflows:** Parallel tool calls and multi-file refactors benefit from improved coding proficiency and parallel execution
- **Multi-turn assistants:** Instruction following and conversational coherence drive task completion across long sessions
- **Auditable agent pipelines:** Higher-quality reasoning traces in thinking mode aid debugging and downstream chain-of-thought data
- **Cost-sensitive production traffic:** The default `medium` thinking level balances quality with throughput
- **Gemini 3 Flash migrations:** Teams on the previous Flash version get the latest coding and agentic improvements without changing tier

## Consider alternatives

- **Deepest reasoning required:** Latency and cost are secondary (consider `google/gemini-3-pro-preview` or `google/gemini-3.1-pro-preview`)
- **Native image generation needed:** Image output is part of the task (consider `google/gemini-3-pro-image` or `google/gemini-3.1-flash-image-preview`)
- **Throughput and budget dominate:** Reasoning depth is not required (consider `google/gemini-3.1-flash-lite-preview`)
- **Sampling parameters required:** Your code depends on `temperature`, `topP`, `topK`, or `thinking_budget`, which Gemini 3.5 Flash does not support

## Frequently asked questions

### What's new in Gemini 3.5 Flash versus Gemini 3 Flash?

Gemini 3.5 Flash improves coding proficiency and supports more reliable parallel agentic execution loops. Core reasoning, instruction following, and multi-turn coherence are all stronger, and thinking-mode outputs include higher-quality reasoning traces.

### How do I control how much Gemini 3.5 Flash thinks before responding?

Set `thinkingLevel` (for example `'high'`) and `includeThoughts: true` under `providerOptions.google.thinkingConfig` when using the AI SDK plus Chat Completions / Responses / Messages APIs. Gemini 3.5 Flash defaults to the `medium` level.

### Which sampling parameters does Gemini 3.5 Flash support?

Gemini 3.5 Flash does not support `temperature`, `topP`, `topK`, or `thinking_budget`. If your application depends on those parameters, evaluate a different model before migrating production traffic.

### Is Gemini 3.5 Flash suitable for agentic coding tasks?

Yes. Improved coding proficiency and parallel agentic execution make Gemini 3.5 Flash well-suited for refactoring services, running concurrent tool calls, and multi-step code transformation workflows where reliability across steps matters.

### Does Gemini 3.5 Flash support streaming?

Yes. Use `streamText` from the AI SDK plus Chat Completions / Responses / Messages APIs with `model: 'google/gemini-3.5-flash'` for streaming responses.

### Do I need a Google Cloud account to use Gemini 3.5 Flash on AI Gateway?

No. AI Gateway manages provider authentication. Connect using a Vercel API key or OIDC token and AI Gateway handles routing to the underlying provider.

### How does Zero Data Retention work with Gemini 3.5 Flash through AI Gateway?

Yes, Zero Data Retention is available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

### When should I use Gemini 3.5 Flash versus Gemini 3.1 Pro?

Choose Gemini 3.5 Flash when Flash-tier latency and cost matter and the task fits within the Flash quality envelope. Choose Gemini 3.1 Pro for the deepest reasoning, long agentic sessions, or finance and spreadsheet workloads that benefit from pro-tier capability.

## Links

- [Model page](https://vercel.com/ai-gateway/models/gemini-3.5-flash)
- [AI Gateway documentation](https://vercel.com/docs/ai-gateway)
- [Provider model documentation](https://ai.google.dev/gemini-api/docs/models)