Optimal Realistic Local AI for Most

Reddit r/LocalLLaMA Tools

Summary

A practical guide for running local AI on consumer GPUs by pairing a large cloud model as an architect with smaller local models as subagents, using tools like OpenRouter and Hermes.

So you’ve got a 3090 or maybe even a 5090? Or more likely a 4060 8GB Ti. You wanna try local AI, you don’t know what it can/can’t do. 1) Install the best model you can. If you have a 3090 or a 5090, that’s Qwen 27b. If it’s a 4060, it’s Qwen 35b-3a. Search this forum, 35b-3a can RIP on an 8GB card. 2) get an open router account. This is the “big brain” that will help you run your local AI. 3) download Hermes agent harness, set up an architect profile that connects to Qwen-3.7 or kimi-K3 or GLM-5.2 on OpenRouter. 4) set up Hermes profiles for coder, worker and browser-reviewer that connect to your local model, be it Qwen-27b or qwen-35b-3a 5) set up your SOUL.md for the architect profile (that is connected to a good model on OpenRouter) to make it VERY CLEAR that its role is to PLAN (this is where local agents can’t touch big models) and launch subagents using the Hermes delegate_task tool. It is the architect and the delegator. Tell it to send out subagents to scan the codebase. Tell it to make a phased implementation plan using subagents. Tell it to write no code, but to use the subagent coders. 6) launch your next Hermes session with: Hermes -p architect (if using the CLI). Execute some prompts and watch it send out sub-tasks for your local AI. 6) profit
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