> ## Documentation Index
> Fetch the complete documentation index at: https://docs.swarms.world/llms.txt
> Use this file to discover all available pages before exploring further.

# Building Agents with xAI (Grok)

> Build Swarms agents on xAI Grok models — Grok 4 and earlier.

xAI's Grok models are frontier reasoning models with strong real-time knowledge, long context windows, and good tool-use performance. Grok 4 is the right pick when you need an alternative to GPT-5.4 or Claude Opus with comparable capability.

## Installation

```bash theme={null}
pip install -U swarms
```

## Environment Setup

```bash theme={null}
export XAI_API_KEY="xai-..."
```

Get an API key at [console.x.ai](https://console.x.ai/).

## Quick Start

xAI models use the `xai/` prefix:

```python theme={null}
from swarms import Agent

agent = Agent(
    agent_name="Grok-Agent",
    model_name="xai/grok-4-0709",
    max_loops=1,
)

print(agent.run("Summarize the case for first-principles thinking in three paragraphs."))
```

## Model Names

| Model     | `model_name`                      | Best for                    |
| --------- | --------------------------------- | --------------------------- |
| Grok 4    | `"xai/grok-4-0709"` or `"grok-4"` | Frontier reasoning, default |
| Grok 2    | `"xai/grok-2-1212"`               | Earlier generation, cheaper |
| Grok Beta | `"xai/grok-beta"`                 | Legacy                      |

## Grok 4 — Frontier Reasoning

For your hardest analytical and planning tasks:

```python theme={null}
from swarms import Agent

agent = Agent(
    agent_name="Grok-Strategist",
    model_name="xai/grok-4-0709",
    system_prompt="You are a senior strategy consultant. Reason first-principles and cite trade-offs.",
    max_loops=1,
)

print(agent.run(
    "Should a B2B SaaS startup with $5M ARR build an in-house data warehouse or use Snowflake?"
))
```

## Tool Use

Grok supports function calling:

```python theme={null}
from swarms import Agent

def get_weather(city: str) -> str:
    """Return the current weather for a city."""
    return f"{city}: 21°C, partly cloudy"

agent = Agent(
    agent_name="Grok-Assistant",
    model_name="xai/grok-4-0709",
    tools=[get_weather],
    max_loops=3,
)

print(agent.run("What's the weather in Tokyo right now?"))
```

## Streaming

```python theme={null}
from swarms import Agent

agent = Agent(
    agent_name="Streaming-Grok",
    model_name="xai/grok-4-0709",
    streaming_on=True,
    max_loops=1,
)

agent.run("Walk me through how proof-of-stake differs from proof-of-work.")
```

## Multi-Provider Pipeline

Mix Grok with other models — for example, Grok for research and Claude for synthesis:

```python theme={null}
from swarms import Agent, SequentialWorkflow

researcher = Agent(
    agent_name="Grok-Researcher",
    model_name="xai/grok-4-0709",
    system_prompt="Gather facts and quotes with citations.",
    max_loops=2,
)

writer = Agent(
    agent_name="Claude-Writer",
    model_name="claude-sonnet-4-6",
    system_prompt="Write a clear executive summary from the research.",
    max_loops=1,
)

pipeline = SequentialWorkflow(agents=[researcher, writer], max_loops=1)
print(pipeline.run("Impact of AI on the global semiconductor supply chain in 2026."))
```

## Production Defaults

```python theme={null}
from swarms import Agent

agent = Agent(
    agent_name="Production-Grok",
    model_name="xai/grok-4-0709",
    max_loops=1,
    persistent_memory=True,
    context_compression=True,
    context_length=128_000,
    autosave=True,
    retry_attempts=3,
    print_on=False,
)
```

## Next Steps

* [Building Agents with OpenAI](/examples/model-providers/openai)
* [Building Agents with Anthropic](/examples/model-providers/anthropic)
* [Model Providers Overview](/integrations/model-providers)