Low to midrange systems (8-32 GB) vs. free cloud tiers (lemmy.frozeninferno.xyz)

submitted 6 days ago by BigHeadMode@lemmy.frozeninferno.xyz to c/localllama@sh.itjust.works

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I'm a noob to local LLMs. I want to use an LLM to create Python and Bash functions from well-defined specs written by me. I've used Claude's Sonnet for this mostly.

I'm a light user of LLMs and almost never hit the request limit on Claude.

It seems like cloud LLMs are in a price war right now and last-gen capabilities are bottoming out in cost? Is that correct?

I pay about $0.12 per kWh, probably going up as more AI data centers get built.

Hardware I have:

<16GB VRAM - AMD BC-250 APU - "16 GB total with approximately 12 GiB assigned to GPU UMA and 4 GiB left for the OS" (hardware unlocking changes by the day)
8GB RAM - 11th gen Intel laptop with Xe graphics
8GB RAM - Pixel 7a
32 GB DDR3 - 2nd gen intel - doubt this does anything

Hardware I'm eventually selling:

8GB VRAM RTX 3070 + 32 GB DDR5 + 1TB NVMe SSD - AMD Ryzen 5 7600X CPU - putting this here in case it's substantially better than the BC-250

Among this hardware, I should look for a model that fits on the BC-250?

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[-] SirDimples@programming.dev 3 points 5 days ago

I'll add my vote to keeping the 32+8 system as that has the most ram.

I also have an 8GB RTX 3070 Ti and 32GB RAM that I run Qwen3.6-35B-A3B perfectly on (30+ t/s) and looking forward to a possible Qwen3.8 35B update.

Recently bought a used 8GB RTX 3070 for a bargain, planning to combine it with the 3070 Ti and hopefully run a lower quant Qwen3.8-27B which is crazy good for its size.

this post was submitted on 21 Aug 2026

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