Can a $60 enterprise GPU turn a 6-watt mini PC into a 100% private, local AI powerhouse?
In this video, I look at the ZimaBoard 2 running AI workloads using an Nvidia Tesla P4 - an old afforable GPU from 2016. I reviewed its performance across local LLMs (Ollama), Stable Diffusion image generation, Immich machine learning, Jellyfin 4K transcoding, and local-network AI coding in VSCode.
And i cover the hardware quirks you have to keep in mind if you want to run the same setup.
Timestamps:
00:00 - Introduction
03:40 - Hardware requirements and modifications
12:07 - Software setup overview - ZimaOS, Docker containers, and configurations
13:59 - Media Apps with a GPU
16:45 - Image Generation with AI - Stable Diffusion
19:07 - LLM Chatbot
24:10 - Coding with Local AI
27:29 - AI assistant coding
28:25 - The Verdict
Things mentioned in the video:
Hardware & OS
ZimaBoard 2: https://www.icewhale.io/zimaboard/
ZimaOS (GitHub): https://github.com/IceWhaleTech/zimaos
Self-Hosted Applications
Jellyfin: https://jellyfin.org/
Immich: https://immich.app/
Stable Diffusion WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui
Ollama: https://ollama.com/
AnythingLLM: https://anythingllm.com/
Open WebUI: https://openwebui.com/
Developer Tools & Extensions
Continue (VS Code Extension): https://www.continue.dev/
Visual Studio Code: https://code.visualstudio.com/
OpenCode Desktop: https://opencode.ai/
AI Models & Weights
Civitai (Stable Diffusion Checkpoints): https://civitai.com/
Hugging Face (Open LLMs): https://huggingface.co/
If you considering buying your own ZimaBoard 2 - use my promo code for 15$ off via:
- Discount code TechFi15 ($15 OFF)
- Purchase link for ZimaBoard 2: https://bit.ly/4ri9Ay7
Also, If you want to support the channel - consider subbing to my Patreon at https://www.patreon.com/c/TechFi
In this video, I look at the ZimaBoard 2 running AI workloads using an Nvidia Tesla P4 - an old afforable GPU from 2016. I reviewed its performance across local LLMs (Ollama), Stable Diffusion image generation, Immich machine learning, Jellyfin 4K transcoding, and local-network AI coding in VSCode.
And i cover the hardware quirks you have to keep in mind if you want to run the same setup.
Timestamps:
00:00 - Introduction
03:40 - Hardware requirements and modifications
12:07 - Software setup overview - ZimaOS, Docker containers, and configurations
13:59 - Media Apps with a GPU
16:45 - Image Generation with AI - Stable Diffusion
19:07 - LLM Chatbot
24:10 - Coding with Local AI
27:29 - AI assistant coding
28:25 - The Verdict
Things mentioned in the video:
Hardware & OS
ZimaBoard 2: https://www.icewhale.io/zimaboard/
ZimaOS (GitHub): https://github.com/IceWhaleTech/zimaos
Self-Hosted Applications
Jellyfin: https://jellyfin.org/
Immich: https://immich.app/
Stable Diffusion WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui
Ollama: https://ollama.com/
AnythingLLM: https://anythingllm.com/
Open WebUI: https://openwebui.com/
Developer Tools & Extensions
Continue (VS Code Extension): https://www.continue.dev/
Visual Studio Code: https://code.visualstudio.com/
OpenCode Desktop: https://opencode.ai/
AI Models & Weights
Civitai (Stable Diffusion Checkpoints): https://civitai.com/
Hugging Face (Open LLMs): https://huggingface.co/
If you considering buying your own ZimaBoard 2 - use my promo code for 15$ off via:
- Discount code TechFi15 ($15 OFF)
- Purchase link for ZimaBoard 2: https://bit.ly/4ri9Ay7
Also, If you want to support the channel - consider subbing to my Patreon at https://www.patreon.com/c/TechFi
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- AI Картинки
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