Qwen2.5-1.5B-Instruct-GGUF

Qwen2.5-1.5B-Instruct-GGUF

Gives you the small Qwen2.5 1.5B chat model as GGUF files in eight quantization sizes, for running with llama.cpp on a laptop or modest GPU. For people who want a light local assistant.

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: This repository holds the instruction-tuned Qwen2.5 1.5B model in GGUF format, made for llama.cpp. You chat with it on your own computer, with no hosted service in between.

The files come in eight quantization types, from q2_K up to q8_0, so you can trade size against quality. The model has 1.54B parameters and a context of 32,768 tokens, with generation of up to 8,192.

Who it suits: It suits people who want a light chat model on their own machine, for drafting, simple code help and structured answers, and who are comfortable with a command line.

Industry | Who uses it | How they use it | Example
Local AI | Enthusiasts | Chat with a small model offline | Ask for a short explanation
Software | Developers | Test a light model inside a local tool | Draft a small script
Education | Students | Practice prompts on modest hardware | Rewrite a paragraph
Research | ML engineers | Compare quant sizes | Check q4 against q8

If you need the strongest answers or extremely long documents, you can skip it, since larger Qwen2.5 models exist.

Where to use it: The files run in llama.cpp on Windows, macOS or Linux. The card suggests the conversation mode for a chatbot-style experience.

• llama-cli from llama.cpp
• A laptop CPU or a GPU with layers offloaded
• Any tool that loads GGUF files

Use case | Who | What they get back
Chatbot-style chat | Everyday users | Replies in a running conversation
Light drafting | Writers | Short text drafts
Size testing | Engineers | Quality across the quant files

How to set it up: You need Python with pip to fetch a file and a working llama.cpp. The card says to clone llama.cpp and install it by its guide, then download the one GGUF file you need.

• Python with pip
• llama.cpp installed
• A few hundred MB to a few GB of disk space, by quant

1. Install the Hugging Face hub package.
2. Download the GGUF file you want, instead of the whole repository.
3. Run it from the llama.cpp folder.

pip install -U huggingface_hub

huggingface-cli download Qwen/Qwen2.5-1.5B-Instruct-GGUF qwen2.5-1.5b-instruct-q5_k_m.gguf --local-dir . --local-dir-use-symlinks False

How to use it: You start llama-cli in conversation mode with the path to your GGUF file, then type to the model. The command also sets the assistant's role, the GPU layers and the reply length.

./llama-cli -m <gguf-file-path> \
    -co -cnv -p "You are Qwen, created by Alibaba Cloud. You are a helpful assistant." \
    -fa -ngl 80 -n 512

Flag | What it does
-m | Points to your GGUF file
-cnv | Starts conversation mode
-p | Sets the system prompt
-ngl | Sets how many layers go to the GPU
-n | Limits the reply length in tokens

Example: You start the command with the q5_k_m file and type a short question in the chat. The model answers in the terminal, and you can keep the conversation going.

For newcomers and experts: If you are new, download the q5_k_m file from the example, run the command and say hello. Then try a smaller or larger quant to see the change.

If you know the field, the model is a transformer that uses rotary position embeddings, SwiGLU and RMSNorm, with a bias on the attention projections and tied word embeddings. It has 28 layers and grouped-query attention with 12 query heads and 2 key-value heads.

Download one GGUF file
Run llama-cli in conversation mode
Type a message
Read the reply

Good to know: The quant sizes run from a 2-bit q2_K up to an 8-bit q8_0, with q3, q4, q5 and q6 options between them. The card points to a blog post with benchmark results, including quantized against bfloat16.

• License: apache-2.0
• Cost to run: none named
• Data it reaches: files you download, and the messages you type
• Not for: users who need the largest Qwen2.5 models, since this is the 1.5B size

On Hugging Face, 13 November 2026

• Task: text generation
• Parameters: 1.8B
• Weights: about 889 MB at 4-bit (estimate)
• Formats: GGUF
• Downloads in the last 30 days: 544,123
• Likes: 200
• License: apache-2.0
• Languages: en
• Based on: Qwen/Qwen2.5-1.5B-Instruct
• Quantized versions: 1
• Fine-tunes: 3
• Tags: gguf, chat, text-generation, conversational

Links

• Model: https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-GGUF
• Files: https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-GGUF/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download Qwen/Qwen2.5-1.5B-Instruct-GGUF

Then follow the usage in its model card. Nothing in this kit runs by itself.