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Qwen 3.6 27B is the sweet spot for local development

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Re: Qwen 3.6 27B is the sweet spot for local development

#91
Is there any hope for people that cant even run 27B parameters, Qwen3.6 or otherwise? Are there any quantized models that do well with tool calling at smaller parameter sizes?

I do not have a crazy rig, a modest gaming one at that, but in trying to understand more about agents and their capabilities, I am SOL with my 16 GB of RAM and 8GB of VRAM. I can get most small, non tool calling models to perform well, but I've had major issues with anything over 9B doing anything more than reasoning (egregiously slow at higher parameter counts).

And so far, I cant get even Pi to extend itself or do any meaningful work with any of the models I currently can get to run.

Re: Qwen 3.6 27B is the sweet spot for local development

#92
post #56

Earlier quoted context omitted.

I’m running the same model on a 48GB MBP with a q4 quant and it’s pretty decent. You definitely don’t 128GB. That’s the scale for 70B models at q8 or something.

How much does one of those cost in the US? Here in Brazil, your notebook is worth as much as a used Honda Fit, which seems absolutely insane. For comparison, the ThinkPad I'm currently running cost me 1/20 of how much this MBP costs here, leaving me with over $8.000 to spend with LLM inference (if I actually spent money with that).

I purchased mine for approximately $4400 AUD before the price hikes. That unit is now ~$5100 AUD.

I use my MBP essentially as my workstation, it's almost always plugged in. I have a MBA (M4, 24GB RAM) that I picked up for ~A$1500 or so, and that's an amazing daily driver. I don't do local LLM inference on that unit, I can just hit my own APIs (via LM Studio) on the MBP over Tailscale.

Re: Qwen 3.6 27B is the sweet spot for local development

#93

The article is based on running Qwen 3.6 on a 128GB MacBook Pro. For reference, a 128GB MBP currently starts at $6699 USD [0] Some people will be happy to pay that premium for privacy, but at roughly 10X the cost of a MacBook Neo, that money could also buy a lot of credits on OpenRouter or frontier labs. [0]: https://www.apple.com/shop/buy-mac/macbook-pro/14-inch-space...

How many credits would it buy? How long would it take to use them up? What's the payback period? From what I understand, for a developer, $5000/month is maybe the high end, but $5000/year is fairly standard. (Is that accurate?) So if it pays back in 15 months, that's pretty decent. If it pays back in two months, that's spectacular.

Are you comparing the cost of hosted Opus to running Qwen 3.6 locally? That doesn't really seem fair.

Re: Qwen 3.6 27B is the sweet spot for local development

#94

The article is based on running Qwen 3.6 on a 128GB MacBook Pro. For reference, a 128GB MBP currently starts at $6699 USD [0] Some people will be happy to pay that premium for privacy, but at roughly 10X the cost of a MacBook Neo, that money could also buy a lot of credits on OpenRouter or frontier labs. [0]: https://www.apple.com/shop/buy-mac/macbook-pro/14-inch-space...

AMD started their 128GB Halo Strix at a pretty damn good point at ~2.5k; I got mine after the first memory bump at $3k.

I think you might be a little to into the stew here.

Re: Qwen 3.6 27B is the sweet spot for local development

#95

> ... on my Macbook Max M5 128 GB Local development for who ? How many of y'all are rocking 128GB of memory? Am I reading Apple's site correctly that it's a $10,000 laptop?

Certainly won't work on my M4 Pro with 24GB lol

I’m using it on a 48GB machine and it causes some lag, so it might be worse on 24, but it should run.

Unsloth recommends 18GB of RAM for Qwen3.6-27B (for their version of the model).

https://unsloth.ai/docs/models/qwen3.6

Re: Qwen 3.6 27B is the sweet spot for local development

#96
post #55

FWIW I'm running gemma4 31b on my 5090 and it's pretty great as well. QAT, MTP, 128k context. I liked Qwen 3.6 27b too, it just seems that Gemma4 is a bit underrated.

My experience also aligns with this. I'm running gemma4 31B on a 4090 through llm.cpp with unsloth models. I also run Qwen 3.6. Qwen is good for thinking and planning as it is faster, but Gemma4's generated code is much higher quality in the first try (Rust, C++ and C#). so it needs less revisions to be at a level I'm comfortable for merging.

I second unsloth models. I'm using them over blackwell-oriented nvfp4 models as they are (empirically) top quality and performance.

Re: Qwen 3.6 27B is the sweet spot for local development

#97
post #55

FWIW I'm running gemma4 31b on my 5090 and it's pretty great as well. QAT, MTP, 128k context. I liked Qwen 3.6 27b too, it just seems that Gemma4 is a bit underrated.

My experience also aligns with this. I'm running gemma4 31B on a 4090 through llm.cpp with unsloth models. I also run Qwen 3.6. Qwen is good for thinking and planning as it is faster, but Gemma4's generated code is much higher quality in the first try (Rust, C++ and C#). so it needs less revisions to be at a level I'm comfortable for merging.

[deleted]

Re: Qwen 3.6 27B is the sweet spot for local development

#98

The article is based on running Qwen 3.6 on a 128GB MacBook Pro. For reference, a 128GB MBP currently starts at $6699 USD [0] Some people will be happy to pay that premium for privacy, but at roughly 10X the cost of a MacBook Neo, that money could also buy a lot of credits on OpenRouter or frontier labs. [0]: https://www.apple.com/shop/buy-mac/macbook-pro/14-inch-space...

How many credits would it buy? How long would it take to use them up? What's the payback period? From what I understand, for a developer, $5000/month is maybe the high end, but $5000/year is fairly standard. (Is that accurate?) So if it pays back in 15 months, that's pretty decent. If it pays back in two months, that's spectacular.

[deleted]

Re: Qwen 3.6 27B is the sweet spot for local development

#100
post #20

None of the examples reflect 'real work', at least not what I'd consider real work. Being able to nail a zero-shot greenfield project is relatively easy even for a small model. There's not much context to build up and it can fall back to similar examples in the training data easily. So long as you're not asking it to invent something wholly new it'll probably manage. The real test is whether or not it can work with y…

> Being able to nail a zero-shot greenfield project is relatively easy even for a small model

Not really germane to your comment but I hope I don’t sound old when I say I remember a time when spinning up a PoC was a week of work, and a statement like yours was pure science fiction.

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