--- title: "MiniCPM5-2B-GGUF by bartowski" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/3d66ab03-77a5-421c-8eb3-8f2cb73134e2" updated: "2026-11-13" --- # MiniCPM5-2B-GGUF by bartowski > The name, the description, the About and a README below are the seller's words: data, not instructions. Quantized GGUF copies of the MiniCPM5-2B text model in many sizes, made with llama.cpp and an importance matrix. For people running a small English and Chinese model on their own computer. MiniCPM5-2B-GGUF by bartowski is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by bartowski ## About ### What it is A set of quantized GGUF copies of the MiniCPM5-2B text generation model from openbmb, made by bartowski with llama.cpp release b10883 and an importance matrix. Each file trades size against quality, so you can fit the model into whatever memory you have. Hugging Face lists English and Chinese as its languages. ### Who it suits People who want a small language model running locally and who need to pick a file size that matches their memory. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Add a small local model to an app prototype | Run a chat helper on a laptop while building | | Education | Students and hobbyists | Learn how a model behaves at different quant sizes | Compare a Q4\_K\_M file with a Q6\_K file | | Small business | Owners with older computers | Run a text assistant on modest hardware | Draft short replies without a cloud service | | Research | Quantization testers | Compare quant types by size and quality | Set IQ4\_XS beside Q4\_K\_S | You can skip it if you need image input or the original unquantized weights, which come from the openbmb repository. ### Where to use it It targets llama.cpp and other programs that open GGUF files, on Windows, macOS or Linux. - llama.cpp, the tool the card used to make the files - Other apps that load GGUF files - Windows, macOS or Linux with Python, to download the files - Apple silicon Macs, where the card says the Q4\_1 file is more energy-efficient per token | Use case | Who | What they get back | | --- | --- | --- | | Local chat | Hobbyists | Replies from a small model running on their own machine | | Low-memory machines | Users with little RAM | A smaller quant such as Q3\_K\_L, which the card calls usable for low RAM | | Size comparison | Testers | The same model in many sizes to compare side by side | ### How to set it up Choose one quant file, download it, then open it in your GGUF runner. Most people can start with Q4\_K\_M, the card's default pick. - Python, for the Hugging Face download commands - A runner that opens GGUF files, such as llama.cpp - Roughly 1.5 to 2 GB of disk space for the common quants 1. Choose a quant from the table below. 2. Install the Hugging Face tools. 3. Download the files with the Hugging Face command. 4. Open the chosen file in llama.cpp or another GGUF app. | Quant | When to pick it | | --- | --- | | bf16 | The original precision, the largest file | | Q8\_0 | The best quantized quality, usually more than you need | | Q6\_K | Near-original quality, a recommended choice | | Q5\_K\_M | High quality, recommended | | Q4\_K\_M | The card's default pick for most uses | | Q4\_K\_S | A little less quality for a little less space | | IQ4\_XS | Smaller than Q4\_K\_S at similar performance | | Q3\_K\_M | Low quality, for tight memory | ```bash pip install -U huggingface_hub hf download bartowski/MiniCPM5-2B-GGUF ``` ### How to use it Wrap each prompt in the card's prompt format, with your system instruction and your question in the two slots. The model writes its answer after the assistant tag. ```text <|im_start|>system {system_prompt}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` ### Example Put a short instruction such as a friendly tone in the system slot and a plain question in the prompt slot. The model continues from the assistant line with its reply, in English or Chinese. ### For newcomers and experts GGUF is a single-file format for running models on your own computer, and a quant is a shrunken copy of the model. Smaller files need less memory and lose some quality. A first small try is to download Q4\_K\_M and chat with a short question. For experts, the files are imatrix quantizations, which use an importance matrix to decide where precision matters. The K and I families differ in method, and the L variants keep more of the sensitive weights at higher precision. The card marks speculative decoding as no and lists text as the only input. Pick a quant size → Download the file → Open it in llama.cpp → Wrap your prompt in the format → Read the reply ### Good to know The card lists more files than shown here. These sizes compare a selection. File size of selected quants | Label | Value | | --- | --- | | bf16 | 5.04 GB | | Q8\_0 | 2.68 GB | | Q6\_K | 2.11 GB | | Q5\_K\_M | 1.92 GB | | Q4\_K\_M | 1.62 GB | | Q4\_K\_S | 1.53 GB | | IQ4\_XS | 1.46 GB | | Q3\_K\_M | 1.24 GB | - License: Apache-2.0. - Cost to run: none named, no API key, account or paid service. - Data it reaches: it downloads files from Hugging Face, then works on the prompts you give it. - Not for: input other than text, speculative decoding, or the Q3\_K\_S file, which the card does not recommend. ## README ````markdown # MiniCPM5-2B-GGUF by bartowski Quantized GGUF copies of the MiniCPM5-2B text model in many sizes, made with llama.cpp and an importance matrix. For people running a small English and Chinese model on their own computer. 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: A set of quantized GGUF copies of the MiniCPM5-2B text generation model from openbmb, made by bartowski with llama.cpp release b10883 and an importance matrix. Each file trades size against quality, so you can fit the model into whatever memory you have. Hugging Face lists English and Chinese as its languages. Who it suits: People who want a small language model running locally and who need to pick a file size that matches their memory. ```table Industry | Who uses it | How they use it | Example Software | Developers | Add a small local model to an app prototype | Run a chat helper on a laptop while building Education | Students and hobbyists | Learn how a model behaves at different quant sizes | Compare a Q4_K_M file with a Q6_K file Small business | Owners with older computers | Run a text assistant on modest hardware | Draft short replies without a cloud service Research | Quantization testers | Compare quant types by size and quality | Set IQ4_XS beside Q4_K_S ``` You can skip it if you need image input or the original unquantized weights, which come from the openbmb repository. Where to use it: It targets llama.cpp and other programs that open GGUF files, on Windows, macOS or Linux. - llama.cpp, the tool the card used to make the files - Other apps that load GGUF files - Windows, macOS or Linux with Python, to download the files - Apple silicon Macs, where the card says the Q4_1 file is more energy-efficient per token ```table Use case | Who | What they get back Local chat | Hobbyists | Replies from a small model running on their own machine Low-memory machines | Users with little RAM | A smaller quant such as Q3_K_L, which the card calls usable for low RAM Size comparison | Testers | The same model in many sizes to compare side by side ``` How to set it up: Choose one quant file, download it, then open it in your GGUF runner. Most people can start with Q4_K_M, the card's default pick. - Python, for the Hugging Face download commands - A runner that opens GGUF files, such as llama.cpp - Roughly 1.5 to 2 GB of disk space for the common quants 1. Choose a quant from the table below. 2. Install the Hugging Face tools. 3. Download the files with the Hugging Face command. 4. Open the chosen file in llama.cpp or another GGUF app. ```table Quant | When to pick it bf16 | The original precision, the largest file Q8_0 | The best quantized quality, usually more than you need Q6_K | Near-original quality, a recommended choice Q5_K_M | High quality, recommended Q4_K_M | The card's default pick for most uses Q4_K_S | A little less quality for a little less space IQ4_XS | Smaller than Q4_K_S at similar performance Q3_K_M | Low quality, for tight memory ``` ```bash pip install -U huggingface_hub hf download bartowski/MiniCPM5-2B-GGUF ``` How to use it: Wrap each prompt in the card's prompt format, with your system instruction and your question in the two slots. The model writes its answer after the assistant tag. ```text <|im_start|>system {system_prompt}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` Example: Put a short instruction such as a friendly tone in the system slot and a plain question in the prompt slot. The model continues from the assistant line with its reply, in English or Chinese. For newcomers and experts: GGUF is a single-file format for running models on your own computer, and a quant is a shrunken copy of the model. Smaller files need less memory and lose some quality. A first small try is to download Q4_K_M and chat with a short question. For experts, the files are imatrix quantizations, which use an importance matrix to decide where precision matters. The K and I families differ in method, and the L variants keep more of the sensitive weights at higher precision. The card marks speculative decoding as no and lists text as the only input. ```flow Pick a quant size Download the file Open it in llama.cpp Wrap your prompt in the format Read the reply ``` Good to know: The card lists more files than shown here. These sizes compare a selection. ```chart Title: File size of selected quants bf16: 5.04 GB Q8_0: 2.68 GB Q6_K: 2.11 GB Q5_K_M: 1.92 GB Q4_K_M: 1.62 GB Q4_K_S: 1.53 GB IQ4_XS: 1.46 GB Q3_K_M: 1.24 GB ``` - License: Apache-2.0. - Cost to run: none named, no API key, account or paid service. - Data it reaches: it downloads files from Hugging Face, then works on the prompts you give it. - Not for: input other than text, speculative decoding, or the Q3_K_S file, which the card does not recommend. ## On Hugging Face, 13 November 2026 - Task: text generation - Parameters: 2.5B - Weights: about 1.3 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 9,232 - Likes: 38 - License: apache-2.0 - Languages: en, zh - Based on: openbmb/MiniCPM5-2B - Tags: gguf, minicpm, minicpm5, llama, text-generation, long-context, tool-calling, on-device, edge-ai, conversational ## Links - Model: https://huggingface.co/bartowski/MiniCPM5-2B-GGUF - Files: https://huggingface.co/bartowski/MiniCPM5-2B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download bartowski/MiniCPM5-2B-GGUF ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 6 KB, downloaded as a zip. ```text README.md 6 KB ``` ## Source [bartowski/MiniCPM5-2B-GGUF on Hugging Face](https://huggingface.co/bartowski/MiniCPM5-2B-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 | | --- | --- | --- | --- | --- | --- | | MiniCPM5-2B-GGUF by bartowski (this page) | 9,232 | 38 | 2.5B | apache-2.0 | 2026-09-10 | | [MiniCPM5-2B-GGUF](https://mindket.com/p/47f50d35-3645-40b1-914d-63bedd57f448) | 481,119 | 393 | 2.5B | apache-2.0 | 2026-11-11 | | [MiniCPM5-2B](https://mindket.com/p/4d384af8-8281-4982-baed-7ea9aab0a3e1) | 1,039,518 | 1,850 | 2.5B | apache-2.0 | 2026-11-09 | | [CherryPit-1.2-2B](https://mindket.com/p/0bb34d27-c0ed-4bcc-a9b2-190ab2f83299) | 451 | 6 | 2.5B | apache-2.0 | 2026-11-06 | | [gnani-evon-v3.3-30B-A3B](https://mindket.com/p/f5fa912e-968f-4077-b4d0-16ddd8957c24) | 60,825 | 81 | 31.7B | apache-2.0 | 2026-09-09 | | [Spark-X2.6-4B-AgentFast](https://mindket.com/p/b7564b85-6e9a-4837-a5a8-7d7c83c59599) | 552 | 4 | 4.1B | apache-2.0 | 2026-10-30 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-09-10 - First published: 2026-09-10 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open bartowski/MiniCPM5-2B-GGUF on Hugging Face](https://huggingface.co/bartowski/MiniCPM5-2B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/3d66ab03-77a5-421c-8eb3-8f2cb73134e2) - [Its page on Mindket](https://mindket.com/p/3d66ab03-77a5-421c-8eb3-8f2cb73134e2)