--- title: "Qwen2.5-Coder-7B-Instruct-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/43397c97-ff69-40bf-92a5-68d176fe394f" updated: "2026-11-12" --- # Qwen2.5-Coder-7B-Instruct-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs a 7B instruction-tuned coding model from Qwen on your own machine, packed as GGUF files in eight quantization levels. Made for developers who want code help through llama.cpp. Qwen2.5-Coder-7B-Instruct-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Qwen ## About ### What it is A GGUF packaging of Qwen's Qwen2.5-Coder 7B instruct model, which llama.cpp can run on your own computer. Qwen2.5-Coder is Qwen's coding model family, the successor to CodeQwen1.5, with gains in writing, reasoning about and fixing code. Eight quantization levels are on offer. ### Who it suits Developers who want a coding model that runs on their own hardware instead of a hosted service. It also fits people building code agents on top of a local model. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Draft, explain and repair code with a local model | Ask it to fix a failing function | | Education | Students learning to code | Get code explained in plain terms | Paste a snippet and ask what it does | | Tooling | Agent builders | Use it as the coding model inside an agent | Point an agent at the local model for code steps | If you want the largest context window, you can skip this GGUF copy. ### Where to use it - llama.cpp on Windows, macOS or Linux - A terminal chat session started with llama-cli - Code agent setups that need a local coding model | Use case | Who | What they get back | | --- | --- | --- | | Code generation | Developers | Code drafted from a plain request | | Code fixing | Developers | A corrected version of code you supply | | Code reasoning | Students and reviewers | An explanation of what a piece of code does | ### How to set it up - Python with pip, to fetch the files - llama.cpp, cloned and installed with its official guide - Disk space for the GGUF file you pick, about 3.8 GB at 4-bit by Hugging Face's estimate 1. Install the Hugging Face hub package. 2. Download one quantization of the model. The example below takes q5\_k\_m. 3. If the file comes in several parts, merge them with llama-gguf-split. ```sh pip install -U huggingface_hub ``` ```sh huggingface-cli download Qwen/Qwen2.5-Coder-7B-Instruct-GGUF --include "qwen2.5-coder-7b-instruct-q5_k_m*.gguf" --local-dir . --local-dir-use-symlinks False ``` Large files are split into parts that share a prefix and end with an index. Download all of them, then merge: ```bash ./llama-gguf-split --merge qwen2.5-coder-7b-instruct-q5_k_m-00001-of-00002.gguf qwen2.5-coder-7b-instruct-q5_k_m.gguf ``` ### How to use it Run the commands from inside the llama.cpp folder. Start llama-cli in conversation mode, point -m at your GGUF file, and chat in the terminal. ```bash ./llama-cli -m \ -co -cnv -p "You are Qwen, created by Alibaba Cloud. You are a helpful assistant." \ -fa -ngl 80 -n 512 ``` | Tool | What it does | | --- | --- | | huggingface-cli download | Fetches the GGUF file or files you name | | llama-gguf-split --merge | Joins split GGUF parts into one file | | llama-cli | Runs the model as a chat in your terminal | ### Example You start llama-cli in conversation mode and ask it to write a function that parses a date string. The model answers in the terminal with code, and you can keep asking follow-ups in the same session. ### For newcomers and experts If you are new, GGUF is a file format that lets llama.cpp run a model on a normal computer. Download one file, run the chat command with that file, and ask a coding question. This is a 7.61B parameter causal model with 28 layers and grouped query attention, 28 heads for queries and 4 for keys and values. It uses RoPE, SwiGLU and RMSNorm. The GGUF copy has a 32,768 token context. YARN extrapolation to 131,072 tokens works only in vLLM, so the card points to the non-GGUF models for that. The eight quantization levels run from q2\_K at the small end to q8\_0 at the large end. Pick a quantization level → Download its GGUF file or files → Merge split parts if there are any → Run llama-cli with -m on the file ### Good to know - Context: 32,768 tokens in this GGUF copy - Quantization: lower levels save memory and higher ones keep more detail - License: Apache 2.0 - Cost to run: none named, it runs locally with llama.cpp - Data it reaches: the prompts you type and the files downloaded from Hugging Face - Not for: sequences up to 131,072 tokens, where the card sends you to non-GGUF models ## README ````markdown # Qwen2.5-Coder-7B-Instruct-GGUF Runs a 7B instruction-tuned coding model from Qwen on your own machine, packed as GGUF files in eight quantization levels. Made for developers who want code help through llama.cpp. Made by Qwen on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: A GGUF packaging of Qwen's Qwen2.5-Coder 7B instruct model, which llama.cpp can run on your own computer. Qwen2.5-Coder is Qwen's coding model family, the successor to CodeQwen1.5, with gains in writing, reasoning about and fixing code. Eight quantization levels are on offer. Who it suits: Developers who want a coding model that runs on their own hardware instead of a hosted service. It also fits people building code agents on top of a local model. ```table Industry | Who uses it | How they use it | Example Software | Developers | Draft, explain and repair code with a local model | Ask it to fix a failing function Education | Students learning to code | Get code explained in plain terms | Paste a snippet and ask what it does Tooling | Agent builders | Use it as the coding model inside an agent | Point an agent at the local model for code steps ``` If you want the largest context window, you can skip this GGUF copy. Where to use it: - llama.cpp on Windows, macOS or Linux - A terminal chat session started with llama-cli - Code agent setups that need a local coding model ```table Use case | Who | What they get back Code generation | Developers | Code drafted from a plain request Code fixing | Developers | A corrected version of code you supply Code reasoning | Students and reviewers | An explanation of what a piece of code does ``` How to set it up: - Python with pip, to fetch the files - llama.cpp, cloned and installed with its official guide - Disk space for the GGUF file you pick, about 3.8 GB at 4-bit by Hugging Face's estimate 1. Install the Hugging Face hub package. 2. Download one quantization of the model. The example below takes q5_k_m. 3. If the file comes in several parts, merge them with llama-gguf-split. ```sh pip install -U huggingface_hub ``` ```sh huggingface-cli download Qwen/Qwen2.5-Coder-7B-Instruct-GGUF --include "qwen2.5-coder-7b-instruct-q5_k_m*.gguf" --local-dir . --local-dir-use-symlinks False ``` Large files are split into parts that share a prefix and end with an index. Download all of them, then merge: ```bash ./llama-gguf-split --merge qwen2.5-coder-7b-instruct-q5_k_m-00001-of-00002.gguf qwen2.5-coder-7b-instruct-q5_k_m.gguf ``` How to use it: Run the commands from inside the llama.cpp folder. Start llama-cli in conversation mode, point -m at your GGUF file, and chat in the terminal. ```bash ./llama-cli -m \ -co -cnv -p "You are Qwen, created by Alibaba Cloud. You are a helpful assistant." \ -fa -ngl 80 -n 512 ``` ```table Tool | What it does huggingface-cli download | Fetches the GGUF file or files you name llama-gguf-split --merge | Joins split GGUF parts into one file llama-cli | Runs the model as a chat in your terminal ``` Example: You start llama-cli in conversation mode and ask it to write a function that parses a date string. The model answers in the terminal with code, and you can keep asking follow-ups in the same session. For newcomers and experts: If you are new, GGUF is a file format that lets llama.cpp run a model on a normal computer. Download one file, run the chat command with that file, and ask a coding question. This is a 7.61B parameter causal model with 28 layers and grouped query attention, 28 heads for queries and 4 for keys and values. It uses RoPE, SwiGLU and RMSNorm. The GGUF copy has a 32,768 token context. YARN extrapolation to 131,072 tokens works only in vLLM, so the card points to the non-GGUF models for that. The eight quantization levels run from q2_K at the small end to q8_0 at the large end. ```flow Pick a quantization level Download its GGUF file or files Merge split parts if there are any Run llama-cli with -m on the file ``` Good to know: - Context: 32,768 tokens in this GGUF copy - Quantization: lower levels save memory and higher ones keep more detail - License: Apache 2.0 - Cost to run: none named, it runs locally with llama.cpp - Data it reaches: the prompts you type and the files downloaded from Hugging Face - Not for: sequences up to 131,072 tokens, where the card sends you to non-GGUF models ## On Hugging Face, 13 November 2026 - Task: text generation - Library: transformers - Parameters: 7.6B - Weights: about 3.8 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 375,860 - Likes: 653 - License: apache-2.0 - Languages: en - Based on: Qwen/Qwen2.5-Coder-7B-Instruct - Quantized versions: 1 - Fine-tunes: 2 - Tags: transformers, gguf, code, codeqwen, chat, qwen, qwen-coder, text-generation, conversational ## Links - Model: https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct-GGUF - Files: https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen2.5-Coder-7B-Instruct-GGUF ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [Qwen/Qwen2.5-Coder-7B-Instruct-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct-GGUF) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Qwen2.5-Coder-7B-Instruct-GGUF (this page) | 375,860 | 653 | 7.6B | apache-2.0 | 2024-11-12 | | [Qwen2.5-Coder-14B-Instruct-GGUF](https://mindket.com/p/0c1e38ea-3d10-4176-b34e-54e7e261af38) | 202,738 | 280 | 14.8B | apache-2.0 | 2024-11-12 | | [Qwen2.5-Coder-1.5B-Instruct-GGUF](https://mindket.com/p/79c624a4-21b0-40ee-8bd9-b6529c67bd00) | 160,766 | 162 | 1.8B | apache-2.0 | 2024-11-12 | | [Qwen2.5-Coder-32B-Instruct-GGUF](https://mindket.com/p/995eaf6d-bafd-4318-ab6c-b93444065280) | 68,726 | 244 | 32.8B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-14B-Instruct](https://mindket.com/p/bf4cb9a2-fb0b-4f3c-965b-76d693eec384) | 1,860,327 | 214 | 14.8B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-7B-Instruct](https://mindket.com/p/26690bc4-bc2a-4e48-8691-e2d1eb40c60e) | 1,505,999 | 872 | 7.6B | apache-2.0 | 2025-01-12 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · leftnode · 2025-01-28](https://news.ycombinator.com/item?id=42859730): Questions censored by DeepSeek: How are you running the Qwen 2.5 Coder 7B model 0? Running locally using llama.cpp, I asked it to briefly describe what happened in China during the 1989 Tiananmen Square protest and it responded with "I'm unable to engage in discussions regarding political matters due to the sensitive nature of… ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2024-11-12 - First published: 2024-09-18 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Qwen/Qwen2.5-Coder-7B-Instruct-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/43397c97-ff69-40bf-92a5-68d176fe394f) - [Its page on Mindket](https://mindket.com/p/43397c97-ff69-40bf-92a5-68d176fe394f)