Laguna XS Model in OpenCode

Poolside AI's Laguna XS model, a small local LLM, performed well in refactoring Rust code via OpenCode, making relatively few errors and handling tool calls correctly except for escaped quotes. The 20.3 GB 4-bit quantized GGUF model outperformed Qwen 3.6 35B, Gemma 4, and North Mini Code in targeted code changes, though it struggled with open-ended optimization tasks.

I am continually interested in having a small, local LLM running in llama-cpp that can edit and add simple features to programs written in Rust and similar languages. Recently support for the Laguna models from Poolside AI an American AI company was added to llama-cpp . I tried out the smaller version Laguna XS locally. I used OpenCode and had the model perform a series of refactoring changes on the code base. It made relatively few errors and almost all of the tool calls worked correctly it became confused with escaped quotes once, and I don't blame it . I used the official GGUF 4-bit quantized model from Poolside on their Hugging Face page, Laguna-XS-2.1-Q4 K M.gguf . It weighed in at 20.3 GB good thing I have fairly fast Internet these days . Overall, I found Laguna XS to perform well , probably better than Qwen 3.6 35B, Gemma 4 and North Mini Code. I started feeling more confident in it, and made a series of refactoring changes which mostly worked correctly. It struggled on an open-ended task "optimize this function" but for more targeted changes, I feel Laguna XS is likely better than the other open-weights models supported by my 12 GB Nvidia GPU.