I added a second GPU just for local AI workloads, and it cost less than upgrading my main one
The author decided to add a second GPU to handle local AI workloads instead of upgrading their primary graphics card. They chose a used RTX 3060 with 12GB VRAM, which was more cost-effective than purchasing a high-end GPU. This setup efficiently runs smaller local language models like Qwen2.5 and Llama 3.2 for tasks such as document analysis and general queries.
- ▪The author uses local LLMs like Qwen2.5 and Llama 3.2 to avoid message limits and censorship on cloud AI services.
- ▪A pre-owned RTX 3060 with 12GB VRAM was sufficient for running 7B–8B parameter models locally.
- ▪Adding a dedicated, older GPU for AI was cheaper than upgrading to a new high-end graphics card.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at XDA Developers.
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