# Google: gemini-3-flash

- Model ID: `gemini-3-flash`
- Provider: Google
- Web version: https://www.moleapi.com/en/models/google/gemini-3-flash
- Content status: verified

## Model introduction

Gemini 3 Flash is the Gemini 3 model for low latency, high throughput, and cost-efficient multimodal work.

## Model capabilities

- OpenAI compatible
- Responses API
- Anthropic compatible
- Gemini compatible
- Vision
- Prompt cache
- Reasoning

### Verified specifications

- Official positioning: Fast, efficient Gemini 3 model
- Context window: Up to 1,000,000 tokens
- Input / output: Text, image, audio, video, PDF / Text
- Best operating profile: Low latency, high throughput, multimodal

## Model pricing and access

Pricing is supplied dynamically by the MoleAPI console API.

### Standard (default, x1)

- Input: $0.5 / 1M tokens
- Output: $3 / 1M tokens
- Cache read: $0.05 / 1M tokens

### Discount (discount, x0.8)

- Input: $0.4 / 1M tokens
- Output: $2.4 / 1M tokens
- Cache read: $0.04 / 1M tokens

### Access protocols

| Protocol | Method | Endpoint |
| --- | --- | --- |
| openai | POST | /v1/chat/completions |
| openai-response | POST | /v1/responses |
| anthropic | POST | /v1/messages |
| gemini | POST | /v1beta/models/{model}:generateContent |

- Live pricing source: https://home.moleapi.com/api/pricing

## About gemini-3-flash

Gemini 3 Flash is the Gemini 3 model for low latency, high throughput, and cost-efficient multimodal work.

### Best for

Real-time chat, moderation, batch extraction, mobile applications, and high-concurrency multimodal processing.

### Core strengths

- Fast responses fit direct interaction and high-concurrency services.
- Natively covers text, image, audio, video, and PDF input.
- Long context and lower cost suit batch document and media tasks.

### Limitations

- Very difficult professional reasoning and quality-first work favor Pro.
- High reasoning effort reduces the latency advantage of a Flash model.

### Selection and production evaluation

Start a gemini-3-flash evaluation by mapping its official positioning to real work: Real-time chat, moderation, batch extraction, mobile applications, and high-concurrency multimodal processing. The first pass should exercise both its main strength, "Fast responses fit direct interaction and high-concurrency services.", and its known limitation, "Very difficult professional reasoning and quality-first work favor Pro.", instead of relying on a single subjective general-chat comparison.

For access, MoleAPI currently lists openai, openai-response, anthropic, gemini protocols and the Standard, Discount billing groups for this Google model; the default price summary is Input $0.5 / 1M tokens · Output $3 / 1M tokens. Pricing, protocols, and groups come from the live catalog, so production planning should still price representative requests using real context length, output size, and cache-hit assumptions.

No independent ranking is shown unless it matches this exact model ID and reasoning profile, so nearby variants are not used as a proxy. Before launch, pin the model ID, prompt, and sample set, then compare task accuracy, structured-output validity, tool-call success, and timeout rates under the same conditions.

The model material on this page was last checked on 2026-07-24. When upstream model cards, context limits, or tool support change, update the cited bilingual facts before changing the recommendation; live MoleAPI price changes remain separate and update from the catalog automatically.

### Sources

- [B.AI Gemini 3 Flash model guide](https://docs.b.ai/llmservice/models/gemini-3-flash/) — B.AI
- [Google Gemini model documentation](https://ai.google.dev/gemini-api/docs/models) — Google
- Last verified: 2026-07-24

## Code examples

### cURL

```bash
curl https://api.moleapi.com/v1/responses \
  -H "Authorization: Bearer $MOLEAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gemini-3-flash","input":"Explain this problem step by step."}'
```

### Python

```python
from openai import OpenAI

client = OpenAI(base_url="https://api.moleapi.com/v1", api_key="YOUR_MOLEAPI_API_KEY")
response = client.responses.create(model="gemini-3-flash", input="Explain this problem step by step.")
print(response.output_text)
```

### TypeScript

```typescript
import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.moleapi.com/v1", apiKey: process.env.MOLEAPI_API_KEY });
const response = await client.responses.create({ model: "gemini-3-flash", input: "Explain this problem step by step." });
console.log(response.output_text);
```

## More related models

- [gemini-3.5-flash](https://www.moleapi.com/en/models/google/gemini-3.5-flash) — Google
- [gemini-3.1-pro](https://www.moleapi.com/en/models/google/gemini-3.1-pro) — Google
- [gemini-3.7-flash](https://www.moleapi.com/en/models/google/gemini-3.7-flash) — Google

## Frequently asked questions

### How is gemini-3-flash priced?

Prices are read from the MoleAPI console API and update with model prices, context tiers, and account groups.

### How can I access gemini-3-flash?

The catalog currently lists openai, openai-response, anthropic, gemini.

### How do I switch an existing project to gemini-3-flash?

Keep the MoleAPI API address and key, replace the model parameter, and check protocol-specific parameters.

### Where do the gemini-3-flash details come from?

Capabilities and limitations are checked against B.AI and the other cited pages; pricing and protocols come from the MoleAPI console.