--- license: mit base_model: LocoreMind/LocoOperator-4B tags: - code - agent - tool-calling - gguf - llama-cpp - qwen --- # LocoOperator-4B-GGUF This repository contains the **official GGUF quantized versions** of [LocoOperator-4B](https://huggingface.co/LocoreMind/LocoOperator-4B). **LocoOperator-4B** is a 4B-parameter code exploration agent distilled from **Qwen3-Coder-Next**. It is specifically optimized for local agent loops (like Claude Code style), providing high-speed codebase navigation with **100% JSON tool-calling validity**. ## 🚀 Which file should I choose? We provide several quantization levels to balance performance and memory usage: | File Name | Size | Recommendation | |-----------|------|----------------| | **LocoOperator-4B.Q8_0.gguf** | 4.28 GB | **Best Accuracy.** Recommended for local agent loops to ensure perfect JSON output. | | **LocoOperator-4B.Q6_K.gguf** | 3.31 GB | **Great Balance.** Near-lossless logic with a smaller footprint. | | **LocoOperator-4B.Q4_K_M.gguf**| 2.50 GB | **Standard.** Compatible with almost all local LLM runners (LM Studio, Ollama, etc.). | | **LocoOperator-4B.IQ4_XS.gguf**| 2.29 GB | **Advanced.** Uses Importance Quantization for better performance at smaller sizes. | ## 🛠 Usage (llama.cpp) To run this model using `llama-cli` or `llama-server`, we recommend a **context size of at least 50K** to handle multi-turn codebase exploration: ### Simple CLI Chat: ```bash ./llama-cli \ -m LocoOperator-4B.Q8_0.gguf \ -c 51200 \ -p "You are a helpful codebase explorer. Use tools to help the user." ``` ### Serve as an OpenAI-compatible API: ```bash ./llama-server \ -m LocoOperator-4B.Q8_0.gguf \ --ctx-size 51200 \ --port 8080 ``` ## 📋 Model Details - **Base Model:** Qwen3-4B-Instruct-2507 - **Teacher Model:** Qwen3-Coder-Next - **Training Method:** Full-parameter SFT (Knowledge Distillation) - **Primary Use Case:** Codebase exploration (Read, Grep, Glob, Bash, Task) ## 🔗 Links - **Main Repository:** [LocoreMind/LocoOperator-4B](https://huggingface.co/LocoreMind/LocoOperator-4B) - **GitHub:** [LocoreMind/LocoOperator](https://github.com/LocoreMind/LocoOperator) - **Blog:** [locoremind.com/blog/loco-operator](https://locoremind.com/blog/loco-operator) ## 🙏 Acknowledgments Special thanks to `mradermacher` for the initial quantization work and the `llama.cpp` community.