Running local models is good now • Hacker News Board

Re: Running local models is good now

#111

Post by Tharre » Tue, Jun 16, 2026, 4:12 PM UTC

I've been running Qwen3.6-35B-A3B (and 3.5 previously) locally and it's a great model for many small tasks, probably a significant chunk of what most normal people are using LLMs for right now.

But for coding in a harness? In my experience it's unusable even for small projects. It just gets hard stuck at every little problem, wasting hundreds of thousands of tokens trying to make a convoluted solution work instead of doing the obvious thing. Or it will spend hours trying to reason through a fairly simple code flow, incrementally adding debug print statements, only to get confused by the output and then editing completely unrelated code that it convinced itself is the problem.

I've tried instead giving Sonnet the problem description and code and have it come up with a detailed plan that Qwen should implement, but doing that actually consumes a significant amount of tokens compared to just telling it to implement everything, and the results are honestly not that much better. There are just too often subtle issues with the plan that Qwen doesn't recognize when implementing, but make the resulting solution it comes up with unusable.

Re: Running local models is good now

#112

Post by daniban » Tue, Jun 16, 2026, 4:13 PM UTC

With Apple silicon and now the RTX Spark there are real discussions whether local AI is the future. The only problem is Western open source models are so far behind. I genuinely feel there's a push to fix this. Gemma is getting more frequent releases and Nvdia is quietly creating very cool small models. I hope both the hardware and models catch up and local really does emerge.

Re: Running local models is good now

#113

Post by QuantumNoodle » Tue, Jun 16, 2026, 4:13 PM UTC

StevenWaterman wrote: post #24

hypfer wrote: post #15

After having been a happy user of Qwen3.6-27B for a few weeks, due to being away from the hardware, I'm currently forced to use Claude Sonnet 4.6 It is such a downgrade. I don't understand how that's even possible. The thing has so many strongly-held opinions I did not ever ask it for, talking just way too much and generally feeling somehow dumber. Of course, being significantly larger, it will encode more knowledge,…

Yep, I daily drive Qwen3.6-27B (including for work), have done pretty much since it came out. IMO it's the only (small-ish, local) model worth using, if you can run it. It might not be as good as Opus at "add X large feature" but I don't want that in a model. I want to do the thinking while it does the typing. And Qwen 3.6 27B is perfectly good at that (while in my experience models like the 35A3B and gemma are signi…

Do you have any resources on hardware necessary for running models and tweaks? I see you mention 2x 3090 and I wanted to do more search on what hardware is satisfactory for what models.

Re: Running local models is good now

#114

Post by heipei » Tue, Jun 16, 2026, 4:14 PM UTC

c0rruptbytes wrote: post #104

I don't know about good, I use a lot of local models and they're still pretty painful to run locally You have dense models (qwen 27b, gemma 31b) who are pretty smart, but pretty slow You have MoE models (gemma 26b, qwen 35b, north mini code 30b) who are pretty fast, but make a lot of mistakes You need a lot of memory to run these well, quantization makes tool calling weaker, so most run at 4 bit quants and are wonder…

Depends on what you mean by "local". On your Macbook, large dense models like Qwen 3.6 27B will be slow, sure. On a local workstation with a dedicated RTX card you can get > 100 tps, which is more than good enough to work with it, and faster than cloud models in many cases.

Re: Running local models is good now

#115

Post by iagooar » Tue, Jun 16, 2026, 4:14 PM UTC

I love running two models locally: qwen3.6 27B 8bit (dense) and qwen3.6 35B 4bit (MoE).

The 27B is the smarter, more reliable one - but it is slower. The 35B is faster, still very smart but below 27B, a bit less reliable. The reason is the MoE - Mixture of Experts architecture, which only activates a subset of parameters, making the model much much faster.

I run the 27B on a MacBook Pro M5 Max + 40 GPU cores + 128GB RAM (well, on this beast I can have 27B + 35B in memory at the same time with headroom for all the other stuff). But because this is a laptop, it is not possible to run local LLMs all the time - it just gets too hot and too loud.

What excites me more: I run the 35B model on a MacMini M4 with 64GB RAM. It is fast, it gets a lot of work done (e.g. it scans, extracts and classifies my emails, it watches the mailbox all the time and does work). I also use it as my private Hermes assistant ("when is the next Starship launch?", "who is playing today at the World Cup? Give me some trivia").

Next step I am planning is a RTX Pro 6000 Blackwell workstation I can put in my basement. I want to run qwen really fast, with multiple threads / prompts / agents at once. And MAYBE if the budget allows, a 2x RTX Pro 6000 setup in order to run DeepSeek v4 flash on it (to run research on it).

Re: Running local models is good now

#116

Post by zozbot234 » Tue, Jun 16, 2026, 4:14 PM UTC

c0rruptbytes wrote: post #104

I don't know about good, I use a lot of local models and they're still pretty painful to run locally You have dense models (qwen 27b, gemma 31b) who are pretty smart, but pretty slow You have MoE models (gemma 26b, qwen 35b, north mini code 30b) who are pretty fast, but make a lot of mistakes You need a lot of memory to run these well, quantization makes tool calling weaker, so most run at 4 bit quants and are wonder…

Maybe we shouldn't be running these models on laptops with their thermally constrained form factor, and we shouldn't expect quick inference on a par with a large cloud-based platform either, at least not for near-SOTA model quality. It's still worth it to avoid becoming massively reliant on centralized services.

Re: Running local models is good now

#117

Post by bityard » Tue, Jun 16, 2026, 4:14 PM UTC

epistasis wrote: post #85

hypfer wrote: post #15

After having been a happy user of Qwen3.6-27B for a few weeks, due to being away from the hardware, I'm currently forced to use Claude Sonnet 4.6 It is such a downgrade. I don't understand how that's even possible. The thing has so many strongly-held opinions I did not ever ask it for, talking just way too much and generally feeling somehow dumber. Of course, being significantly larger, it will encode more knowledge,…

> talking just way too much OMG this is such an annoying property, just shut the hell up please, and be concise. I suspect that this is an artifact of the thinking property, but please just summarize the thinking process far more concisely, where a single sentence answer is more than sufficient the frontier models seem devoted to going on to a minimum of 5 paragraphs and offering 3-5 new directions. And requests to p…

I'm not sure to what degree you can influence how a model thinks, but you can definitely hide the thinking tokens and tell the model how you want it to talk to you.

For example, the Claude web UI has an Instructions field where I have told it never to congratulate or praise me for asking questions. Earlier Copilot models used a ridiculous number of emoji and bullet lists when answering literally every prompt, I told it to knock that off and prefer detailed paragraphs in prose.

Local agents/frameworks/whatever all have their equivalents for overall user preferences.

Re: Running local models is good now

#118

Post by greenavocado » Tue, Jun 16, 2026, 4:14 PM UTC

c0rruptbytes wrote: post #104

I don't know about good, I use a lot of local models and they're still pretty painful to run locally You have dense models (qwen 27b, gemma 31b) who are pretty smart, but pretty slow You have MoE models (gemma 26b, qwen 35b, north mini code 30b) who are pretty fast, but make a lot of mistakes You need a lot of memory to run these well, quantization makes tool calling weaker, so most run at 4 bit quants and are wonder…

4 bit unsloth quants are good if you never ask for more than 20k context, use it as autocomplete on steroids, and never delegate serious questions to it

Re: Running local models is good now

#119

Post by TkTech » Tue, Jun 16, 2026, 4:15 PM UTC

sathackr wrote: post #30

rmunn wrote: post #7

This is the kind of thing that Anthropic et al should be worried about. As it becomes easier and easier to run local models, the ceiling of what they'll be able to charge will get lower and lower. Not that nobody will be willing to pay $$$$$ per month, but a lot of people are going to multiply the per-month charge by 12 or 24 and say "Could I set up a local model for less than that, and have it pay for itself within…

The opposite of that has been happening for 20 years now with cloud compute. It won't happen with AI models either. It's almost ingrained in the American business model now. Outsource everything. Nobody wants to manage a room full of servers when they can spend 2-3x as much and outsource that headache along with the responsibility for it. Same will happen with AI. Whether that means paying Anthropic that premium or p…

For many companies (country-dependent) that's not really why they use cloud services vs purchasing. It's tax shenanigans and business process overhead. OpEx vs CapEx, and a small (%) bump in the huge AWS bill no one will even notice or a $30k+ invoice for hardware that has to go through rigorous review and 3 departments.

Same reason people pay for things through the AWS marketplace (like Vanta) instead of having to go through their invoicing process.

Re: Running local models is good now

#120

Post by giancarlostoro » Tue, Jun 16, 2026, 4:15 PM UTC

StevenWaterman wrote: post #58

giancarlostoro wrote: post #36

Earlier quoted context omitted.

There's a model on Huggingface where someone takes Qwen and makes it think Opus style, and that one seems to be decent, not sure if they have the 27B variant in that style. I do wonder if you can tweak your system prompt to force Qwen to behave better?

You read the OP backwards, they said Sonnet is a downgrade from Qwen, and prefer Qwen's tone

Sure, but my argument still holds, the idea is that Qwen reasons the way that Opus on High (what is now Max or whatever?) level thinking to reason about problems instead of its standard approach.