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Suggest a model...
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this post was submitted on 09 Aug 2026
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LocalLLaMA
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What are you wanting to do with the model?
Agentic development with that setup, you can easily run a good quant of Qwen3.6-27B at full context. unsloth/Qwen3.6-27B-MTP Q5_K_XL and use a fixed template
Creative writing? Probably need a different model. I’ve heard good things about Gemma 4 31B.
Both of those are dense models so won’t be as fast as Qwen3.6-35B-A3B. Also play around with MTP, quants, KV cache quant, KV caching, etc.
The RAM size will limit you on larger models unless you stream from storage.
More chats i guess, maybe also agents in the future, i am keep to explore that but not yet there.
It's funny; I was just reading about someone who went the other way
https://bitworking.org/news/2026/05/surprising-things-i-learned-putting-together-a-home-brain/
At a certain point, it becomes less about parameters and more about tools supporting those parameters. Something like Pithagoras, Understory, MCP tools etc.
https://github.com/thecodacus/pithagoras/
https://github.com/thecodacus/understory
https://www.youtube.com/watch?v=fpvF4n32lsE
https://www.youtube.com/watch?v=IwN-eK1s8og
This is very interesting, i have saved your comment, it feels too soon for my understanding of it all, but both understory and pithagoras feels less obscure than what would have been, to me, only a few weeks ago.
For sure. Feel free to ask questions, too.
The TL;DR I will leave you with is this; some of what we consider as "smarts" in a LLM has traditionally done by brute force - bigger GPU , more parameters.
The alternative approach is to make the llm do less by itself, but instead, call on other tools. That way, you can squeeze out much more from a smaller llm or weaker hardware, so long as the llm is obedient at tool calling.
Think of it like doing arithmetic in your head vs using a calculator. Both provide the answer, but the latter requires much less brain power.