# gemini-3.5-flash — API, Pricing & Context Window | Vivgrid

> Source: https://vivgrid.com/docs/models/gemini-3.5-flash

gemini-3.5-flash on Vivgrid: Google's fast multimodal model with a 1M-token context window across text, image, video, audio and PDF.

`gemini-3.5-flash` is Google's fast, fully multimodal model, accepting **text, image, video, audio, and PDF** inputs within a **1M-token context window**. It's a strong agent model for workflows that mix media types at scale.

On Vivgrid, `gemini-3.5-flash` runs as a globally centralized model reachable through the same OpenAI-compatible endpoint and unified key as every other model in the catalog.

## Specifications

| Field | Value |
| --- | --- |
| Provider | Google |
| Model ID | `gemini-3.5-flash` |
| Best for | General-purpose |
| Available on | Chat Completions |
| Context window | 1,000,000 tokens |
| Max output | 65,536 tokens |
| Modalities | Text, Image, Video, Audio, PDF |
| Tool / function calling | Yes |
| Knowledge cutoff | 2025-01 |
| Acceleration | Global (centralized) |

## Pricing

Pricing in USD per 1M tokens.

| Input | Cached input | Output |
| --- | --- | --- |
| $1.50 | $0.15 | $9.00 |

### What one request costs

The rates above applied to a 20K-token prompt with a 2K-token reply — a typical single agent turn, small enough that every request is billed at the base rate.

| Request | Cost |
| --- | --- |
| Cold prompt, nothing cached | $0.0480 |
| Warm prompt, 90% of the input served from cache | $0.0237 |


## API surfaces

The Vivgrid Console catalogs `gemini-3.5-flash` on one surface, all behind the same API key. The endpoint shown is the one the Console previews for that surface.

| Surface | Primary endpoint | Use it for |
| --- | --- | --- |
| Chat Completions | `/chat/completions` | Agent projects, where Vivgrid injects the model, system prompt and tools server-side, and Model API calls that name the model per request. |

## Quick start

Get an API key from the Vivgrid Console (https://console.vivgrid.com), then call `gemini-3.5-flash` directly.

```bash
curl https://api.vivgrid.com/v1/chat/completions \
  -H "Authorization: Bearer $VIVGRID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.5-flash",
    "messages": [
      { "role": "user", "content": "Say hello in English, Chinese and Spanish." }
    ],
    "stream": true
  }'
```


## Ideal use cases

- Multimodal agents combining video, audio, images, and PDFs
- Long-context understanding up to 1M tokens
- Fast, high-volume reasoning and summarization
- Media-heavy ingestion and analysis pipelines

## Related models

- [gpt-6-astra](/docs/models/gpt-6-astra) — OpenAI's frontier gpt-6 coding model
- [gemini-4-argon](/docs/models/gemini-4-argon) — Google's flagship Gemini 4 model for coding
- [gemini-3.6-flash](/docs/models/gemini-3.6-flash) — prior flash generation