KAT-Coder-V2.5-Dev GGUF

KAT-Coder-V2.5-Dev GGUF

Imatrix GGUF quantizations of Kwaipilot's KAT-Coder-V2.5-Dev, a 34.7B text model, with 4-bit files of about 19 GB or more. For people who run a large coder-named model locally.

Made by bartowski 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 GGUF quantizations of KAT-Coder-V2.5-Dev from Kwaipilot, a 34.7B text model with English and Chinese listed. A third party made the files with llama.cpp and an importance matrix, so the model runs in many local tools. The name points to a coding model, but the card does not say so itself.

Who it suits: It suits people who run large local models, mainly for code help, and who can pick a file size that fits their memory.

Industry | Who uses it | How they use it | Example
Software | Developers | Run a large coding-oriented model on their own machine | Asking for a function in the chat window
Local AI | Enthusiasts | Chat with a 34.7B model offline | Trying the Q4_K_M file
Research | Evaluators | Compare quant sizes of one model | Measuring Q5_K_M against Q4_K_M
Tool building | Tool authors | Test their app against a large local model | Connecting it to LM Studio or koboldcpp

If your machine has little memory, you can skip it, since the 4-bit files listed are about 19 GB or more.

Where to use it: The card lists several apps that read GGUF files.

• llama.cpp and ramalama
• LM Studio, koboldcpp, Jan AI and Atomic Chat
• Text Generation Web UI and LoLLMs
• Windows, macOS or Linux with Python, to download the files

Use case | Who | What they get back
Coding help | Developers | Code and explanations from a local model
Local chat | Enthusiasts | Replies without a hosted service
Quant comparison | Evaluators | Quality against size across files

How to set it up: You need one GGUF file and an app that loads it. The card warns that a newly supported model may need an update from the app's developers first.

• One of the apps listed above
• A file that fits your memory, with Q4_K_M as the card's default size
• Python, only for the Hugging Face download command

1. Pick a file from the table.
2. Download that one file, not the whole repository.
3. Load it and use the prompt format below.

Title: Some files in the card
Quant | Size | Use
bf16 | 69.38 GB | Full weights, stored in split parts
Q8_0 | 36.91 GB | Top quality, more than most people need
Q6_K | 30.05 GB | Near-perfect quality, recommended
Q5_K_M | 25.02 GB | High quality, recommended
Q4_K_M | 21.39 GB | Good quality, the default for most uses
IQ4_XS | 18.81 GB | Decent quality in a smaller file

pip install -U huggingface_hub
hf download bartowski/Kwaipilot_KAT-Coder-V2.5-Dev-GGUF

How to use it: Wrap each chat in the layout below. The assistant turn opens with a think tag, so the model reasons before it answers.

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
<think>

Example: You load the Q4_K_M file in LM Studio, set a short system prompt, and ask for a small function that removes duplicates from a list. The model thinks first, then writes the function.

For newcomers and experts: A quantized file stores a model's numbers more coarsely to save space. Start with Q4_K_M and one short prompt, then move to a bigger or smaller file if you need to.

For experts, the quants were built with llama.cpp release b10087 and an importance matrix from the author's own dataset. Q6_K_L, Q5_K_L and Q4_K_L keep embedding and output weights at Q8_0. Q4_0 and IQ4_NL offer online repacking for CPU inference.

The original model is converted to GGUF
An importance matrix guides the quantization
Several sizes are written, from bf16 to smaller
You download one file that fits your memory
You load it in an app and send prompts

Good to know: The bf16 files come in split parts. Hugging Face estimates the 4-bit weights near 17.3 GB.

Title: File size by quant type
bf16: 69.38 GB
Q8_0: 36.91 GB
Q6_K: 30.05 GB
Q5_K_M: 25.02 GB
Q4_K_M: 21.39 GB
IQ4_XS: 18.81 GB

• License: Apache 2.0, as Hugging Face lists it
• Cost to run: none named
• Data it reaches: your prompts, run locally, and the files you download
• Not for: small machines, since the files listed run from 18.81 GB up to 69.38 GB

On Hugging Face, 13 November 2026

• Task: text generation
• Parameters: 34.7B
• Weights: about 17.3 GB at 4-bit (estimate)
• Formats: GGUF
• Downloads in the last 30 days: 234,191
• Likes: 148
• License: apache-2.0
• Languages: en, zh
• Based on: Kwaipilot/KAT-Coder-V2.5-Dev
• Tags: gguf, code, agent, agentic-coding, coding, text-generation, imatrix, conversational

Links

• Model: https://huggingface.co/bartowski/Kwaipilot_KAT-Coder-V2.5-Dev-GGUF
• Files: https://huggingface.co/bartowski/Kwaipilot_KAT-Coder-V2.5-Dev-GGUF/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download bartowski/Kwaipilot_KAT-Coder-V2.5-Dev-GGUF

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