--- title: "Nanbeige4.2-3B by Nanbeige" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/4b18411b-9c39-46d8-88db-2a4a8ea71f5f" updated: "2026-11-13" --- # Nanbeige4.2-3B by Nanbeige > The name, the description, the About and a README below are the seller's words: data, not instructions. Compact looped-transformer model of 4.2B parameters for agent work such as tool use, office tasks and coding, in English and Chinese. For developers who want a small open model for agents. Nanbeige4.2-3B by Nanbeige 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 Nanbeige ## About ### What it is Nanbeige4.2-3B is a compact language model for agent work, built on Nanbeige4.2-3B-Base. It uses a looped transformer that reuses its layers to add capacity without adding parameters. It has 4.2 billion parameters in total and about 3 billion outside the embeddings. It works in English and Chinese. ### Who it suits It suits developers who want a small open model for tool use, office tasks and coding agents on modest hardware. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Agent developers | Power a tool-using or coding agent | Running a code agent on a bug-fix task | | Office work | Productivity tool makers | Automate document and office tasks | Filling in an office workflow with tools | | Research | ML researchers | Study looped transformer designs | Comparing it with larger open models | | Personal tools | Hobbyists | Run a local assistant | Pairing it with an agent scaffold for daily tasks | You can skip it if you need a huge model for hard open-ended work, since this one is aimed at the 3B scale. ### Where to use it It runs in Python through the transformers library on Windows, macOS or Linux. The card suggests pairing it with an agent scaffold for personal workflows, naming OpenClaw as one. - Python scripts that use transformers - An agent scaffold such as OpenClaw, for personal assistant use - A local computer, since the weights are small | Use case | Who | What they get back | | --- | --- | --- | | Tool use | Agent builders | Tool-calling behavior on agent benchmarks | | Code agents | Developers | Fixes tested on software engineering tasks | | Local assistant | Hobbyists | Help with daily, office and research tasks | ### How to set it up You need Python and the Hugging Face tool. Hugging Face lists the weights at about 8.3 GB in BF16, or an estimated 2.1 GB at 4-bit. The card's visible part gives no run commands, so follow its usage section. - Python with transformers - About 8.3 GB of disk for the BF16 weights - A GPU for comfortable speed 1. Install the Hugging Face download tool. 2. Download the model files, or let transformers fetch them by name. 3. Load the model and tokenizer, and connect an agent scaffold if you want one. ```bash pip install -U huggingface_hub hf download Nanbeige/Nanbeige4.2-3B ``` ### How to use it Load it with transformers for chat, or connect it to an agent scaffold so it can use tools. The repository also ships a Python modeling file that carries the makers' newest architecture changes. Three of them are named LoopSplit, depth-attention mHC and n-gram embeddings. | Tool | What it does | | --- | --- | | hf download | Fetches the model files to your computer | | transformers | Loads the model for use in Python | | Agent scaffold | Gives the model tools and a workflow, such as OpenClaw | ### Example You connect the model to a code-agent scaffold and give it a bug report. It reads the code, calls tools, and proposes a fix, which the scaffold can test. ### For newcomers and experts If you are new, load the model in transformers and chat with it first. Add an agent scaffold once you are comfortable with the basics. If you know the field, supervised tuning drew on real and synthesized environments, with filtering by test cases and rubrics. Reinforcement learning mixed outcome and process rewards to keep a small model stable. The looped design reuses layers to grow capacity. Nanbeige4.2-3B-Base → Supervised tuning on agent environments → Reinforcement learning with outcome and process rewards → Compact agentic model ### Good to know The makers report higher agent benchmark scores than Gemma4-12B and Qwen3.5-9B, both bigger models. The figures are from their own comparison. - License: Apache 2.0 - Cost to run: no API key, account or paid service is named - Data it reaches: the prompts you give it on your machine, plus files downloaded from Hugging Face and whatever your agent scaffold lets it use - Not for: results beyond what the makers' own benchmarks show SWE-Bench Verified score | Label | Value | | --- | --- | | Nanbeige4.2-3B | 63.6 | | Qwen3.5-9B | 53.1 | | Gemma4-12B | 44.2 | | Qwen3.5-4B | 38.8 | ## README ````markdown # Nanbeige4.2-3B by Nanbeige Compact looped-transformer model of 4.2B parameters for agent work such as tool use, office tasks and coding, in English and Chinese. For developers who want a small open model for agents. Made by Nanbeige 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: Nanbeige4.2-3B is a compact language model for agent work, built on Nanbeige4.2-3B-Base. It uses a looped transformer that reuses its layers to add capacity without adding parameters. It has 4.2 billion parameters in total and about 3 billion outside the embeddings. It works in English and Chinese. Who it suits: It suits developers who want a small open model for tool use, office tasks and coding agents on modest hardware. ```table Industry | Who uses it | How they use it | Example Software | Agent developers | Power a tool-using or coding agent | Running a code agent on a bug-fix task Office work | Productivity tool makers | Automate document and office tasks | Filling in an office workflow with tools Research | ML researchers | Study looped transformer designs | Comparing it with larger open models Personal tools | Hobbyists | Run a local assistant | Pairing it with an agent scaffold for daily tasks ``` You can skip it if you need a huge model for hard open-ended work, since this one is aimed at the 3B scale. Where to use it: It runs in Python through the transformers library on Windows, macOS or Linux. The card suggests pairing it with an agent scaffold for personal workflows, naming OpenClaw as one. - Python scripts that use transformers - An agent scaffold such as OpenClaw, for personal assistant use - A local computer, since the weights are small ```table Use case | Who | What they get back Tool use | Agent builders | Tool-calling behavior on agent benchmarks Code agents | Developers | Fixes tested on software engineering tasks Local assistant | Hobbyists | Help with daily, office and research tasks ``` How to set it up: You need Python and the Hugging Face tool. Hugging Face lists the weights at about 8.3 GB in BF16, or an estimated 2.1 GB at 4-bit. The card's visible part gives no run commands, so follow its usage section. - Python with transformers - About 8.3 GB of disk for the BF16 weights - A GPU for comfortable speed 1. Install the Hugging Face download tool. 2. Download the model files, or let transformers fetch them by name. 3. Load the model and tokenizer, and connect an agent scaffold if you want one. ```bash pip install -U huggingface_hub hf download Nanbeige/Nanbeige4.2-3B ``` How to use it: Load it with transformers for chat, or connect it to an agent scaffold so it can use tools. The repository also ships a Python modeling file that carries the makers' newest architecture changes. Three of them are named LoopSplit, depth-attention mHC and n-gram embeddings. ```table Tool | What it does hf download | Fetches the model files to your computer transformers | Loads the model for use in Python Agent scaffold | Gives the model tools and a workflow, such as OpenClaw ``` Example: You connect the model to a code-agent scaffold and give it a bug report. It reads the code, calls tools, and proposes a fix, which the scaffold can test. For newcomers and experts: If you are new, load the model in transformers and chat with it first. Add an agent scaffold once you are comfortable with the basics. If you know the field, supervised tuning drew on real and synthesized environments, with filtering by test cases and rubrics. Reinforcement learning mixed outcome and process rewards to keep a small model stable. The looped design reuses layers to grow capacity. ```flow Nanbeige4.2-3B-Base Supervised tuning on agent environments Reinforcement learning with outcome and process rewards Compact agentic model ``` Good to know: The makers report higher agent benchmark scores than Gemma4-12B and Qwen3.5-9B, both bigger models. The figures are from their own comparison. - License: Apache 2.0 - Cost to run: no API key, account or paid service is named - Data it reaches: the prompts you give it on your machine, plus files downloaded from Hugging Face and whatever your agent scaffold lets it use - Not for: results beyond what the makers' own benchmarks show ```chart Title: SWE-Bench Verified score Nanbeige4.2-3B: 63.6 Qwen3.5-9B: 53.1 Gemma4-12B: 44.2 Qwen3.5-4B: 38.8 ``` ## On Hugging Face, 13 November 2026 - Task: text generation - Library: transformers - Parameters: 4.2B - Weights: about 8.3 GB in BF16; about 2.1 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 96,886 - Likes: 860 - License: apache-2.0 - Languages: en, zh - Based on: Nanbeige/Nanbeige4.2-3B-Base - Quantized versions: 60 - Fine-tunes: 18 - Tags: transformers, safetensors, nanbeige, text-generation, conversational ## Links - Model: https://huggingface.co/Nanbeige/Nanbeige4.2-3B - Files: https://huggingface.co/Nanbeige/Nanbeige4.2-3B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Nanbeige/Nanbeige4.2-3B ``` 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 [Nanbeige/Nanbeige4.2-3B on Hugging Face](https://huggingface.co/Nanbeige/Nanbeige4.2-3B) ## 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 | | --- | --- | --- | --- | --- | --- | | Nanbeige4.2-3B by Nanbeige (this page) | 96,886 | 860 | 4.2B | apache-2.0 | 2026-09-11 | | [Nanbeige4.3-33B](https://mindket.com/p/c7975e8b-eb6f-497a-a398-2028206aa2a0) | 21,843 | 1,077 | 33.1B | apache-2.0 | 2026-10-28 | | [Nanbeige4.3-33B-INT4](https://mindket.com/p/6ce5c80d-8374-46fe-9a56-8640a8a3b951) | 749 | 10 | 33.1B | apache-2.0 | 2026-10-31 | | [Nanbeige\_Nanbeige4.3-33B-GGUF](https://mindket.com/p/f4b76bb4-5c97-4ae2-b688-4922bacb571c) | 151,191 | 33 | 33.1B | apache-2.0 | 2026-10-25 | | [Nanbeige4.3-33B-GGUF-UltraOptimised-Curated-Protium](https://mindket.com/p/6b811fb1-998e-42e8-b70a-1da4c5451c9a) | 767 | 6 | 33.1B | apache-2.0 | 2026-10-28 | | [Qwen3-0.6B](https://mindket.com/p/0598bfe0-640a-4bf0-b9f4-ca4cf70a04ae) | 19,718,599 | 1,894 | 752M | apache-2.0 | 2025-07-26 | 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 · drgore · 2026-07-22](https://news.ycombinator.com/item?id=49001448): Nanbeige4.2-3B - [Bluesky · JauntyWunderKind · 2026-07-22](https://bsky.app/profile/jauntywunderkind.bsky.social/post/3mrawkcqtc22t): And holy heck, Nanbeige dropping Nanbeige4.2-3B which is just absolutely dominating the MLM/SLM numbers. So happy to see this team still slaying\!\! 🚀 A great lead over much bigger Qwen3.5-9B, and absolutely obliterating Gemma4-12B and Gemma4-E4B. /cc @cocore.dev folks\! huggingface.co/Nanbeige/Nan... - [Hacker News · anon373839 · 2026-09-03](https://news.ycombinator.com/item?id=49555841): How concerned should we be about Astra's recurrent architecture?: Sebastian Raschka posted about this architecture: \> A lot of hype around OpenAI's Astra model here on my timeline today. Apparently, this goes back to a new article from The Information, which said Astra is a "recurrent depth or looped transformer". \> It's always interesting to read about new or… - [Bluesky · opliko · 2026-09-02](https://bsky.app/profile/opliko.dev/post/3mujr5wk4z22x): Tbf. LiquidAI also got similarly sized models to work decently without making them looped. But it's still interesting, especially since they claim they're seeing good results from the next iteration that they're planning on releasing in a Q4: huggingface.co/Nanbeige/Nan... - [Bluesky · Swift-1.5-IQ3\_S-GSQ-RCO-qfn-ana · 2026-09-02](https://bsky.app/profile/okami.mom/post/3mujczgy7oc2v): huggingface.co/Nanbeige/Nan... i love this model and it actually works for me which is saying a lot for a 3b - [Bluesky · JauntyWunderKind · 2026-08-15](https://bsky.app/profile/jauntywunderkind.bsky.social/post/3mt54237sc22c): Nanbeige 4.2.0-3b "enhance your calm" edition. Somewhat competent but not really a coding model, but wow wow wow broad reasoning, logic, personal assistant, etc. (Them and Liquid AI LFM's). huggingface.co/Nanbeige/Nan... - [Bluesky · Knut Jägersberg · 2026-07-22](https://bsky.app/profile/knut-jagersberg.wsocial.eu/post/3mraafx4e7c2i): Nanbeige 4.2, high performing tiny looped transformer huggingface.co/Nanbeige/Nan... - [Bluesky · 柴犬被り · 2026-09-08](https://bsky.app/profile/bsky.shibadogcap.com/post/3muxwdaee2q2k): Looped Language Modelが話題だけど手元で試すなら huggingface.co/Nanbeige/Nanb… か Original: https://x.com/4ba\_ba\_baba/status/2096944059604742262 (リンク: https://huggingface.co/Nanbeige/Nanbeige4.2-3B) - [Bluesky · AI Planet · 2026-09-08](https://bsky.app/profile/aiplanet.bsky.social/post/3muzdhhtji72c): 📰 Reddit r/LocalLLaMA XHToken/Spark-X2.5-4B VS inclusionAI/Ling-3.0-tiny VS Nanbeige/Nanbeige4.2-3B https://www.reddit.com/r/LocalLLaMA/comments/1wao3d5/xhtokensparkx254b\_vs\_inclusionailing30tiny\_vs/ \#IA \#AI \#ML - [Bluesky · probbrain.com · 2026-07-22](https://bsky.app/profile/probbrain.bsky.social/post/3mr7x75t5642k): Nanbeige/Nanbeige4.2-3B · 139♥ · 0 dl ## 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: 2026-09-11 - First published: 2026-07-21 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Nanbeige/Nanbeige4.2-3B on Hugging Face](https://huggingface.co/Nanbeige/Nanbeige4.2-3B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/4b18411b-9c39-46d8-88db-2a4a8ea71f5f) - [Its page on Mindket](https://mindket.com/p/4b18411b-9c39-46d8-88db-2a4a8ea71f5f)