Try Poolside Laguna XS.2: The Free Local AI Coding Agent

What Is Poolside Laguna XS.2?

Poolside Laguna XS.2 is a free, Apache 2.0-licensed AI coding model that you can run entirely on your local machine. No API keys, no recurring fees, no internet required after download. It's a 33-billion parameter Mixture of Experts model with 3 billion active parameters, specifically designed for agentic coding tasks.

Unlike cloud-based coding assistants, everything stays on your machine. Your code, your context, your data — completely private.

How to Install and Run It

The fastest way to get started is through Ollama:

# Pull the model
ollama pull laguna-xs.2

# Start coding
ollama run laguna-xs.2

Alternatively, download directly from Hugging Face and use your preferred inference engine. The model works with popular frameworks like vLLM, llama.cpp, and MLX.

For a full IDE-like experience, try Poolside's "shimmer" — a web-based coding environment optimized for mobile and desktop use with Laguna models.

What Can It Do?

Laguna XS.2 is built for agentic coding workflows, meaning it goes beyond simple code completion:

• Write and modify code across multiple files
• Debug and fix errors by analyzing stack traces and context
• Use third-party tools and APIs autonomously
• Take multi-step actions to complete complex tasks

It's particularly strong for developers who need AI assistance but can't send proprietary code to external APIs.

Why Choose Local Over Cloud AI?

Local AI coding tools offer three advantages that cloud services can't match:

1. Zero recurring cost — No per-token charges, no subscription fees
2. Complete privacy — Your code never leaves your machine
3. Offline capability — Works anywhere, including air-gapped environments

The trade-off is that local models generally offer lower capability than frontier cloud models for the most complex tasks. But for everyday coding, the gap is closing fast.

Common Questions (FAQ)

Q1: What hardware do I need? A1: A Mac with Apple Silicon (M1+) or a PC with an NVIDIA GPU with 8GB+ VRAM. Quantized versions work on even modest hardware.

Q2: Can I use it commercially? A2: Yes. The Apache 2.0 license permits commercial use with attribution. No restrictions on output ownership.

Q3: How do I fine-tune it for my codebase? A3: Use standard fine-tuning frameworks like Hugging Face Transformers or Axolotl. The MoE architecture with 3B active parameters makes fine-tuning relatively efficient on consumer hardware.

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