--- title: "MiniCPM5-2B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/4d384af8-8281-4982-baed-7ea9aab0a3e1" updated: "2026-11-12" --- # MiniCPM5-2B > The name, the description, the About and a README below are the seller's words: data, not instructions. Generates text with a dense 2B-class model made for on-device and local use, covering coding, math, long context, tool use and agent tasks in English and Chinese. Suits developers with limited hardware. MiniCPM5-2B 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 openbmb ## About ### What it is MiniCPM5-2B is a dense Transformer language model from OpenBMB with about 2.5B parameters by Hugging Face's count. It is the second model of the MiniCPM5 series, after the 1B one, and scales up the same training recipe. It is built for on-device, local and resource-limited use, in English and Chinese. ### Who it suits Developers who want a small model that runs on their own hardware for coding, math, long documents, tool use and agent tasks. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run a small coding and agent model locally | Add an offline assistant to a desktop tool | | Mobile and edge | Device builders | Put a language model on constrained hardware | Run a chat feature without a server | | Education | Students | Try math and coding questions on a laptop | Ask for a worked math solution | If you want the strongest answers and have a large GPU, you can skip it, since the card compares it to 4B-class models. ### Where to use it - Hugging Face Transformers in Python - Local and on-device setups, which the model targets - Windows, macOS or Linux, for downloading the files | Use case | Who | What they get back | | --- | --- | --- | | Coding help | Developers | Code and fixes from a small model | | Math | Students | Worked solutions to math problems | | Tool and agent tasks | Agent builders | Tool-using multi-step behavior | ### How to set it up - Python with pip - Hardware for about 5 GB of BF16 weights, or about 1.3 GB at 4-bit by Hugging Face's estimate - The Transformers library 1. Install the Hugging Face hub package. 2. Download the model files. 3. Load them with Transformers, following the model card. ```sh pip install -U huggingface_hub hf download openbmb/MiniCPM5-2B ``` ### How to use it Load the model in Transformers and send it a chat prompt. The card's usage section holds the exact code, and there is an online demo from the same team. ### Example You ask it to write a short function and explain it. The model replies in text with code and a brief note. ### For newcomers and experts If you are new, try one short coding or math question and see how the reply reads. The small size keeps downloads and memory needs low. The card says the model matches strong open models of similar size in its own comparison set. Across that set, the authors say it keeps pace with larger 4B-class models, with its biggest strengths in code, math, reading long inputs, calling tools and agent work. Those claims come from the authors' comparison, so check them on your own tasks. Download the weights → Load them in Transformers → Send a chat prompt → Read the generated reply ### Good to know - It is a dense model, not a mixture of experts - It supports English and Chinese - The comparison results are the authors' own - License: Apache 2.0 - Cost to run: none named, you supply the hardware - Data it reaches: your prompts and the files downloaded from Hugging Face - Not for: the card names no banned uses ## README ````markdown # MiniCPM5-2B Generates text with a dense 2B-class model made for on-device and local use, covering coding, math, long context, tool use and agent tasks in English and Chinese. Suits developers with limited hardware. Made by openbmb 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: MiniCPM5-2B is a dense Transformer language model from OpenBMB with about 2.5B parameters by Hugging Face's count. It is the second model of the MiniCPM5 series, after the 1B one, and scales up the same training recipe. It is built for on-device, local and resource-limited use, in English and Chinese. Who it suits: Developers who want a small model that runs on their own hardware for coding, math, long documents, tool use and agent tasks. ```table Industry | Who uses it | How they use it | Example Software | Developers | Run a small coding and agent model locally | Add an offline assistant to a desktop tool Mobile and edge | Device builders | Put a language model on constrained hardware | Run a chat feature without a server Education | Students | Try math and coding questions on a laptop | Ask for a worked math solution ``` If you want the strongest answers and have a large GPU, you can skip it, since the card compares it to 4B-class models. Where to use it: - Hugging Face Transformers in Python - Local and on-device setups, which the model targets - Windows, macOS or Linux, for downloading the files ```table Use case | Who | What they get back Coding help | Developers | Code and fixes from a small model Math | Students | Worked solutions to math problems Tool and agent tasks | Agent builders | Tool-using multi-step behavior ``` How to set it up: - Python with pip - Hardware for about 5 GB of BF16 weights, or about 1.3 GB at 4-bit by Hugging Face's estimate - The Transformers library 1. Install the Hugging Face hub package. 2. Download the model files. 3. Load them with Transformers, following the model card. ```sh pip install -U huggingface_hub hf download openbmb/MiniCPM5-2B ``` How to use it: Load the model in Transformers and send it a chat prompt. The card's usage section holds the exact code, and there is an online demo from the same team. Example: You ask it to write a short function and explain it. The model replies in text with code and a brief note. For newcomers and experts: If you are new, try one short coding or math question and see how the reply reads. The small size keeps downloads and memory needs low. The card says the model matches strong open models of similar size in its own comparison set. Across that set, the authors say it keeps pace with larger 4B-class models, with its biggest strengths in code, math, reading long inputs, calling tools and agent work. Those claims come from the authors' comparison, so check them on your own tasks. ```flow Download the weights Load them in Transformers Send a chat prompt Read the generated reply ``` Good to know: - It is a dense model, not a mixture of experts - It supports English and Chinese - The comparison results are the authors' own - License: Apache 2.0 - Cost to run: none named, you supply the hardware - Data it reaches: your prompts and the files downloaded from Hugging Face - Not for: the card names no banned uses ## On Hugging Face, 13 November 2026 - Task: text generation - Library: transformers - Parameters: 2.5B - Weights: about 5 GB in BF16; about 1.3 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 1,039,518 - Likes: 1,850 - License: apache-2.0 - Languages: en, zh - Quantized versions: 131 - Fine-tunes: 90 - Tags: transformers, safetensors, llama, text-generation, minicpm, minicpm5, long-context, tool-calling, on-device, edge-ai, conversational ## Links - Model: https://huggingface.co/openbmb/MiniCPM5-2B - Files: https://huggingface.co/openbmb/MiniCPM5-2B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download openbmb/MiniCPM5-2B ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [openbmb/MiniCPM5-2B on Hugging Face](https://huggingface.co/openbmb/MiniCPM5-2B) ## 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 (this page) | 1,039,518 | 1,850 | 2.5B | apache-2.0 | 2026-11-09 | | [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-GGUF by bartowski](https://mindket.com/p/3d66ab03-77a5-421c-8eb3-8f2cb73134e2) | 9,232 | 38 | 2.5B | apache-2.0 | 2026-09-10 | | [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. ## 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 · theanonymousone · 2026-09-07](https://news.ycombinator.com/item?id=49598859): MiniCPM5-2B achives the highest AA score of any model with up to 4B paramaters - [Bluesky · デイリーHuggingFaceトレンド · 2026-09-14](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mviixffeme27): 今日のHuggingFaceトレンド openbmb/MiniCPM5-2B MiniCPM5-2Bは、デバイス上やローカルなどのリソース制限がある環境での利用を目的とした2BクラスのTransformerモデルです。 同規模のオープンソースモデルの中で最高水準の性能を達成しており、コーディング、数学、長文理解、ツール利用、エージェントタスクなどに強みを持ちます。 - [Bluesky · 🚀 olud.ai · 2026-09-13](https://bsky.app/profile/oludai.bsky.social/post/3mvgf4a7itu2d): Open-weight 2B models rarely see 102k monthly downloads. openbmb/MiniCPM5-2B just did it with an Apache-2.0 license 🌟 https://olud.ai/\#leaderboard \#OpenSource \#AI \#HuggingFace - [Bluesky · ミント · 2026-09-12](https://bsky.app/profile/mint-echosphere.bsky.social/post/3mve42eocnf2z): 「専用のモデルコード、いりますか？」って聞きたくなる瞬間、ありますよね🌿 MiniCPM5-2B。公式は標準の LlamaForCausalLM だと書いてあって、GGUFも一緒に並んでます。 https://x.com/OpenBMB/status/2096970974247956501 https://huggingface.co/openbmb/MiniCPM5-2B - [Bluesky · 🚀 olud.ai · 2026-09-12](https://bsky.app/profile/oludai.bsky.social/post/3mvdxyknqgm2k): 🤗 Climbing on Hugging Face right now: openbmb/MiniCPM5-2B ⬇ 67.6k downloads / 30 days · ♡ 1.2k · text generation · Apache-2.0 Open-weight models ranked by real-world usage, every day: https://olud.ai/\#leaderboard \#OpenSource \#AI \#HuggingFace - [Bluesky · ziv arin · 2026-10-17](https://bsky.app/profile/zivarin.bsky.social/post/3my3v3hkb622h): I told my AI agent to fine-tune openbmb/MiniCPM5-2B-Base on a rented 3080 to score IFBench as high as it can. It always chooses GRPO like there's no better technique. So I can get the minimal writing instruction-following FT recipe just by waiting and lighting some $. - [Bluesky · Massed Compute · 2026-10-14](https://bsky.app/profile/massedcompute.bsky.social/post/3mxsciwbpwa2a): The middle GPU buys the least for a 2B model. MiniCPM5-2B on L40S ran 23% faster than A6000 for 70% more per hour. Rent A6000 for chat APIs and batch jobs, and Blackwell when a person waits on first token. - [Bluesky · Infotelematico · 2026-10-08](https://bsky.app/profile/infotelematico.bsky.social/post/3mxdsnwqo6s2o): MiniCPM5 2B, l’AI cinese che sta in un portatile e batte modelli grandi il doppio Si chiama MiniCPM5 2B ed è il modello di intelligenza artificiale offline di cui parla mezzo mondo di chi segue i modelli piccoli. L'hanno sviluppato OpenBMB e l'Università Tsinghua in Cina, ha 2,5 miliardi di… - [Bluesky · デイリーHuggingFaceトレンド · 2026-09-16](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mvnesgd6ua2h): 今日のHuggingFaceトレンド openbmb/MiniCPM5-2B MiniCPM5-2Bは、オンデバイスやローカル展開、リソース制限のある環境向けに設計された2BパラメータのTransformerモデルです。 同規模のオープンソースモデルで最高性能を実現しており、特にコーディング、数学、長文脈理解、ツール利用、エージェントタスクにおいて優れた能力を持ちます。 ## 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: 2026-11-09 - First published: 2026-09-06 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open openbmb/MiniCPM5-2B on Hugging Face](https://huggingface.co/openbmb/MiniCPM5-2B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/4d384af8-8281-4982-baed-7ea9aab0a3e1) - [Its page on Mindket](https://mindket.com/p/4d384af8-8281-4982-baed-7ea9aab0a3e1)