[Models](/models) / [Qwen 2.5 32B](/models?family=Qwen%202.5%2032B#models-gallery) / OpenHands LM 32B v0.1 ![Qwen logo](/model-logos/qwen.svg) # Run OpenHands LM 32B v0.1 on Mac OpenHands LM 32B v0.1 runs 100% private on Mac inside Private LLM — no internet connection required, no data sent to any server. 32.8BMac ## Download the quantized weights These are the exact GPTQ-Int4 weights Private LLM runs for OpenHands LM 32B v0.1, published on our Hugging Face org. They're standard weights you can load in any app that supports the format, not just Private LLM. - [Mac — GPTQ-Int4 →](https://huggingface.co/numen-tech/openhands-lm-32b-v0.1-GPTQ-Int4) ## Specifications Parameters 32.8B Context window 33K tokens License MIT Quantization GPTQ-Int4 Family Qwen 2.5 32B ## What OpenHands LM 32B v0.1 is good at [coding](/models/coding) OpenHands LM is a 32 billion parameter open source coding model that you can download and run on your own hardware. It is fine-tuned to solve software engineering tasks, especially fixing issues on GitHub, and achieves strong results on the SWE Bench Verified benchmark. The model is designed to let developers use capable coding agents locally without relying on external API services. ## Which of your devices can run it ### Mac Mac (Apple Silicon, 192GB)MacBook Pro (M4 Max, 128GB)Mac Studio / Pro (Apple Silicon, 96GB)MacBook Pro (M4 Max, 64GB)MacBook Pro (M4 Max, 48GB)MacBook Pro (M4 Max, 36GB)Mac (Apple Silicon, 32GB)MacBook Air (M4, 24GB) Browse every model that fits [iPhone](/models/best-for-iphone) or [Mac](/models/best-for-mac). ## How to run OpenHands LM 32B v0.1 in Private LLM 1. Download Private LLM from the App Store. 2. Open the in-app model library and choose OpenHands LM 32B v0.1. 3. Download the model once, then chat fully offline. [![Download Private LLM on the App Store](/app-store/download-badge/en/download.svg)![Download Private LLM on the App Store](/app-store/download-badge/en/download-dark.svg)](/download)[Join our Discord](/discord) ## Variants & related models ![Qwen logo](/model-logos/qwen.svg) ### EVA Qwen2.5 32B v0.2 32.8B creative 131K contextMac [View details →](/models/eva-qwen2.5-32b-v0.2) ![Qwen logo](/model-logos/qwen.svg) ### Qwen 2.5 32B 32.8B general 33K contextMac [View details →](/models/qwen2.5-32b-instruct) ![Qwen logo](/model-logos/qwen.svg) ### Qwen 2.5 Coder 32B 32.8B coding 33K contextMac [View details →](/models/qwen2.5-coder-32b-instruct) ![Mistral logo](/model-logos/mistral.svg) ### CodeNinja 1.0 OpenChat 7B 7.2B coding 8K contextiPhone & iPad · Mac [View details →](/models/codeninja-1.0-openchat-7b) ![Meta logo](/model-logos/meta.svg) ### Llama 3 WhiteRabbitNeo 8B v2.0 8B coding 8K contextiPhone & iPad · Mac [View details →](/models/llama-3-whiterabbitneo-8b-v2.0) ![Qwen logo](/model-logos/qwen.svg) ### OpenHands LM 7B v0.1 7.6B coding 33K contextiPhone & iPad [View details →](/models/openhands-lm-7b-v0.1) ## Frequently asked questions - Can I run OpenHands LM 32B v0.1 on iPhone? OpenHands LM 32B v0.1 is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline. - Can I run OpenHands LM 32B v0.1 on Mac? Yes. OpenHands LM 32B v0.1 runs on Macs with enough unified memory, such as Mac (Apple Silicon, 192GB), MacBook Pro (M4 Max, 128GB), Mac Studio / Pro (Apple Silicon, 96GB), MacBook Pro (M4 Max, 64GB), MacBook Pro (M4 Max, 48GB), MacBook Pro (M4 Max, 36GB), Mac (Apple Silicon, 32GB), MacBook Air (M4, 24GB), fully on-device in Private LLM. - Does OpenHands LM 32B v0.1 work offline? Yes. Once downloaded in Private LLM, OpenHands LM 32B v0.1 runs 100% on-device — no internet connection, and nothing is sent to any server. - Is OpenHands LM 32B v0.1 free to use? Private LLM is a one-time purchase with no subscription and no per-message cost. The models themselves are open source — once downloaded, they run offline with nothing to pay per use. ## Why run OpenHands LM 32B v0.1 in Private LLM Private LLM has run local AI on iPhone, iPad, and Mac since 2023, before Apple Intelligence existed. Inference happens on your device, so your OpenHands LM 32B v0.1 conversations never reach a server. The part most apps gloss over is quantization, and that is exactly where on-device quality is won or lost. Most llama.cpp and MLX wrappers ship the same off-the-shelf 4-bit RTN weights. Private LLM ships GPTQ and OmniQuant quantization, tuned per model, and our 3-bit OmniQuant models match or beat those 4-bit RTN builds on the same Apple Silicon. Run the same model both ways and you feel it in the first reply. [See how our quantization works](/en/faq#Why-can-t-Private-LLM-load-models-directly-from-Hugging-Face). ### More from Numen [![Slop or Not app icon](/app-icons/slop-or-not.png) #### Slop or Not Catch AI-written text on iPhone and Mac. The check runs on-device, so nothing you paste gets uploaded. ](https://slopornot.ai)[![Clean Links app icon](/app-icons/clean-links.png) #### Clean Links Strip trackers and clutter from any link before you share it. The cleanup happens on your device. ](https://cleanlinks.app) Specifications and summary come from OpenHands LM 32B v0.1's [Hugging Face model card](https://huggingface.co/all-hands/openhands-lm-32b-v0.1), released under the MIT license. Private LLM ships its own quantized models, built with GPTQ-Int4 quantization tuned per model, and isn't affiliated with the model's authors.