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Nativ: Run frontier open models locally on your Mac

blaizzy.github.io

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Re: Nativ: Run frontier open models locally on your Mac

#72
post #7

Is „frontier“ overused? I thought frontier models were the best-of-the-best such as Fable right now. I assume you can’t host these models yourself since you would need many GB of RAM and expensive GPU of is my thinking of „frontier models“ wrong?

I was confused too, but I believe that it refers to the Pareto Frontier: the best set of solutions to a multi-objective problem.

Look it up, it’s a bit difficult to explain concisely in words but it is intuitive visually.

If we are thinking of intelligence and price, a model will be in the Pareto Frontier if there’s no cheaper model of the same or higher intelligence. Or if there’s no more intelligent model for that price or lower.

EDIT: See this chart from Artificial Analysis: https://artificialanalysis.ai/#intelligence-comparison-tabs

So for example DeepSeek V4 Pro can be considered a frontier model because there's no cheaper model that is as intelligent.

For any solution in the Pareto Frontier, there no "no-brainer" alternative, in the sense that there's no other option that is better in some way without giving up something else. It's the best of its "weight-class".

Re: Nativ: Run frontier open models locally on your Mac

#73

Earlier quoted context omitted.

That's not what people are normally referring to when they say "frontier models". It means the most capable models full stop. Not the most capable that you can run locally.

true but tfa's title says "frontier open models"

Frontier open models are Kimi K3, GLM 5.2, DeepSeek V4 Pro, etc. They're all too big to fit on most Macs.

Re: Nativ: Run frontier open models locally on your Mac

#74
post #16

I'm surprised that their home page basically acts as if LM Studio and others don't already do this. It's not clear what the difference is from a glance. It also omits Open WebUI. I've been running Deepseek V4 Flash locally on my Macbook Pro for weeks using Open WebUI + DS4.

"The other “local AI” apps you’ve heard of? They’re proprietary shells built on top of open-source engines they don’t own."

This is a roundabout way of addressing LM Studio.

Re: Nativ: Run frontier open models locally on your Mac

#75

Looking forward to giving this a try. I have tried MLX using Rapid MLX however the LLM (Qwen) would always have hiccups and get stuck repeating itself. Moving onto llama.cpp I was able to get faster tokens with MTP and a more reliable llm. I wonder what other people's experiences are using MLX vs llama.cpp

FWIW on my M1 Max I have not really seen any advantage at all from MLX.

I am fully prepared to believe the benefits accrue more to the M3 and up (because of changes to the Apple Neural Engine).

But with the models I've tested, unless I am missing something, the performance of GGUFs in llama.cpp has been better in some cases.

I still have not had results from Gemma 4's MTP be really worth it, to be honest; but with the Qwen 3.6 MoE it is measurable. Maybe with newer kit it is more meaningful.

(There is every chance that the above is not the experience of anyone who really deeply knows what they are doing; it feels like I am a perpetual novice at this stuff)

Re: Nativ: Run frontier open models locally on your Mac

#76

To clarify, this MIT-licensed app is from the very same dev, 'Prince Canuma', who maintains the popular MLX-VLM library ( https://github.com/Blaizzy/mlx-vlm ). MLX-VLM is a long-time dependency of the excellent LM Studio and others because it can provide faster inference on Apple devices than llama.cpp. Historically, MLX is a smaller community than CUDA, but has some of the fastest updates upon the release of new mod…

its a wrapper around mlx, so thats gonna be the portability bottleneck

Re: Nativ: Run frontier open models locally on your Mac

#77

To clarify, this MIT-licensed app is from the very same dev, 'Prince Canuma', who maintains the popular MLX-VLM library ( https://github.com/Blaizzy/mlx-vlm ). MLX-VLM is a long-time dependency of the excellent LM Studio and others because it can provide faster inference on Apple devices than llama.cpp. Historically, MLX is a smaller community than CUDA, but has some of the fastest updates upon the release of new mod…

I was so excited when I saw "blaizzy" in the domain, because Prince Canuma's work around MLX has been of such uniquely high quality.

Re: Nativ: Run frontier open models locally on your Mac

#78
post #16

I'm surprised that their home page basically acts as if LM Studio and others don't already do this. It's not clear what the difference is from a glance. It also omits Open WebUI. I've been running Deepseek V4 Flash locally on my Macbook Pro for weeks using Open WebUI + DS4.

What spec is your macbook? I want to run Deepseek V4 Flash but its too slow for agents on my Strix Halo.

Re: Nativ: Run frontier open models locally on your Mac

#79
post #47

Genuinely curious: what are people using these smaller local models for? They are getting decently capable, but they are still small enough that I don't trust them for "real" work outside of a handful of fun toy projects. Are people actually using them in coding agents? Or are they mostly using them for other things?

[flagged]

Re: Nativ: Run frontier open models locally on your Mac

#80

To clarify, this MIT-licensed app is from the very same dev, 'Prince Canuma', who maintains the popular MLX-VLM library ( https://github.com/Blaizzy/mlx-vlm ). MLX-VLM is a long-time dependency of the excellent LM Studio and others because it can provide faster inference on Apple devices than llama.cpp. Historically, MLX is a smaller community than CUDA, but has some of the fastest updates upon the release of new mod…

I would also note that for people who want to download these models, you can find MLX versions of just about everything popular on huggingface these days. For instance go look at the "main" page for Qwen 3.6 35B-A3B and then follow the link to quantizations, and pick one of the more popular/reputable MLX variants.

https://huggingface.co/Qwen/Qwen3.6-35B-A3B

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