> ## Documentation Index
> Fetch the complete documentation index at: https://thethirdpenco-feat-tool-lifecycle-events.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# groq()

> Create a Groq language model

Factory function to create a Groq model instance. Groq provides ultra-fast inference for open-source models through an OpenAI-compatible API.

## Signature

```python theme={null}
def groq(model_id: str, *, api_key: str | None = None) -> LanguageModel
```

## Parameters

<ParamField path="model_id" type="str" required>
  The Groq model identifier (e.g., "llama-3.3-70b-versatile", "mixtral-8x7b-32768").
</ParamField>

<ParamField path="api_key" type="str" optional>
  Groq API key. Falls back to `GROQ_API_KEY` environment variable.
</ParamField>

## Returns

A `LanguageModel` instance configured for Groq.

## Environment

Requires `GROQ_API_KEY` environment variable.

```bash theme={null}
export GROQ_API_KEY="gsk_..."
```

## Available Models

| Model ID                  | Description                      |
| ------------------------- | -------------------------------- |
| `llama-3.3-70b-versatile` | Llama 3.3 70B - best quality     |
| `llama-3.1-8b-instant`    | Llama 3.1 8B - ultra fast        |
| `mixtral-8x7b-32768`      | Mixtral 8x7B - 32k context       |
| `gemma2-9b-it`            | Gemma 2 9B - Google's open model |

## Example

```python theme={null}
from ai_query import generate_text
from ai_query.providers import groq

result = await generate_text(
    model=groq("llama-3.3-70b-versatile"),
    prompt="Hello, world!"
)
```

## Provider Options

```python theme={null}
result = await generate_text(
    model=groq("llama-3.3-70b-versatile"),
    prompt="Be creative.",
    provider_options={
        "openai": {
            "temperature": 0.9,
            "max_tokens": 1000
        }
    }
)
```