erikkahlera month ago
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 models, particularly in models with modalities beyond text-in, text-out (vision, STT, TTS, video gen). See also (https://github.com/Blaizzy/mlx-audio-swift). Would be totally unsurprised if those modalities and models get integrated into this UI.
Possibly vibe-coded landing page notwithstanding, the app is mostly written in Swift language. That suggests it will be easy to port this inference stack to iPad and iPhone.
walrus01a month ago
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.
sgt101a month ago
converting a model to MLX is trivially easy as well - just a couple of lines of code and a few minutes wait.
I do find that it reliably crashes on the first try, but then it picks up from where it finishes and completes the conversion reliably.
simonwa month ago
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.
T0mSIlvera month ago
[flagged]
justatdotina month ago
Hi Simon, sorry to spam your comments but 7 months ago you asked me for a media report to back a claim I made and this week it finally arrived. perhaps a little late to be very useful to anyone who maintains that gating function, but here nonetheless:
https://ntindependent.com.au/scientist-says-ministers-pole-f...
dosticka month ago
What
rahimnathwania month ago
Would be totally unsurprised if those modalities and models get integrated into this UI.
Support for dedicated audio-only and image-generation-only models is coming soon.
Der_Einzigea month ago
Switching to mlx-vlm is basically harmful since it (like vllm and sglang) have such garbage support for modern samplers. To be clear, I am one of the authors on the min_p paper, and if min_p is the best you have (when llamacpp supports the far superior top-n-sigma), than I have no reason to switch even if you are somehow faster.
(https://arxiv.org/abs/2411.07641)
And if you do care to support modern samplers, you can start with the following:
1. https://arxiv.org/abs/2509.23234
woadwarrior01a month ago
Thanks for bringing this up. You're 100% right. But most people, even technical ones are oblivious to how much of a difference modern samplers and higher quality quantization algorithms make for on-device LLM inference and are stuck with good old top-p, top-k samplers and RTN quantization.
TBF mlx-vlm does support min-p sampling, but none of the other modern samplers that you list. Ollama and LM Studio are even worse with only top-p and top-k samplers.
trollbridgea month ago
Thanks for that. My first question was “What does this do that Unsloth doesn’t?”
recursivegirtha month ago
LM Studio is trash on Windows / Linux... guess that makes sense...
Forgeties79a month ago
What makes it trash on Linux? I’m a pretty casual user myself so my guess is I haven’t bumped against these limitations. I also don’t have high expectations as I’m running it on a 9070 lol
layla5alivea month ago
Prince CacheAsNUMA? Nice :)
carterschonwalda month ago
its a wrapper around mlx, so thats gonna be the portability bottleneck
moonteara month ago
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?
oersteda month ago
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".
avazhia month ago
That’s not what frontier means.
There are two frontier labs - OpenAI and Anthropic, and maybe 4 frontier models currently. That term refers to model capacity and in general represents a model’s capability relative to the rest of the industry irrespective of price. That’s why even the Qwen announcement carries language about it being ‘near frontier’. Same with Kimi.
Whether a model is frontier or not has everything to do with capability and nothing to do with price.
jboss10a month ago
I think this is one of the easiest to understand.
oersteda month ago
That’s a good visualization, although I am a bit mistrustful of Arena’s scores. It does get around the fact that models are getting trained for the benchmarks, but the methodology of letting random people compare outputs side-by-side is a very shallow judgement method in my opinion.
EDIT: Indeed looking at the overall rankings for text again, the list is rather strange, a lot more about writing style than intelligence.
jboss10a month ago
They supposedly have a style control system, but I doubt it's perfect. I wish there was a parento view like this for agentic systems(using a standard harness)
moonteara month ago
Very interesting rabbit hole for today. Thanks for mentioning Pareto frontier!
andsoitisa month ago
The subtitle on their website is: "Nativ puts frontier intelligence on your desk".
Also, the title is "Run AI models locally on your Mac," not "Run frontier open models locally on your Mac."
dofma month ago
I don't know that I agree with this specific use of frontier because it is confusable as you say.
But (off on a tangent) I do think that there are multiple frontiers generally — and I also think the open weights, small local model frontier is by far the most important and exciting one.
I keep mucking about with what Gemma 4 12B can do and every time I do I find myself thinking that all the energies in the AI world are going in entirely the wrong direction, because it is small, clever, efficient and remarkable.
If all of that research money were to be spent on improving AI models that fit inside a 16GB RAM machine with unified memory, I think really important progress could be made.
I enjoy using the Qwen 3.6 models (and BottleCap's new fine tune of the 27B) but the small Gemma 4 models are impressive in a way that I think is going quite unreported.
So while I don't think this website should use the word "frontier" here, even referring to Qwen 3.6 27B which is weirdly close, I think it could.
lukevpa month ago
I’ve got a 32 gig m1 MacBook Pro. how would I go about trying Gemma like you mentioned? Would it run at an acceptable speed, and what could I do? Coding?
rahimnathwania month ago
brew install llama.cpp
llama-server -hf unsloth/gemma-4-12b-it-GGUF:UD-Q8_K_XLbrody_hamera month ago
“docker run open-webui:ollama” is a simple way to start.
Don’t expect much for coding. But it’s great for general knowledge, rubber ducking, image classification…
dofma month ago
I figure it might be quite a competent general coding teacher for more, er, consumer programming languages, for want of a better word — python, PHP, JS. Seems to be pretty solid on WP knowledge too.
And I find it curiously interesting when talking about photography. I've been finding it intriguing to ask it about my own photos and make suggestions about other images to research. I just showed it three of my own photos, and asked it to analyse them and recommend photographers I should research. It recommended someone amazing I have never heard of before. But it also recommended a 19th century British photographer who happens to be my lifelong photographic hero — someone whose broad characteristics inform what I do without me slavishly copying them. Bit of a jaw-dropping moment for it to have picked up their influence in subject matter that they would never have approached.
I'm still suggesting it more to people for them to see what the small-model future might look like, because it's so much more capable than one might expect.
dofma month ago
On an M1 Max I have been using either Unsloth Studio (which is basically a web app) or LM Studio (nicer app on the Mac). You can use the Google AI Edge Gallery to play with the smaller Gemma models (but at the moment the QAT variants don't seem to be there unless I am missing something).
I think it's likely the 26B QAT model won't fit in your machine — you may be able to fit one of the UD_Q3 or UD_Q2 variants but whether you'll be able to run other things you want at the same time, I don't know.
(The QAT models are "quantization aware training" — AIUI the model weights have been assigned during training to survive four-bit quantization with less loss.)
So what I would recommend trying is this model:
https://huggingface.co/unsloth/gemma-4-12B-it-qat-GGUF
Try UD Q4_K_M maybe.
(I don't think the M1 really gets much benefit from MLX, in case you were wondering, though I could be wrong)
My interest in this model is largely to really get to grips with what small models can actually do, especially with tool calling, because I think it helps comprehend what the value proposition of the cloud models is.
I have been very surprised by the quality and clarity of its answers. It's also helped me understand that much of a typical harness system prompt is likely to be unnecessary now; Gemma 4 seems to be pretty sensible out of the box.
You're absolutely not going to be able to get it to go off and build whole apps from a long prompt; it is not that good, but it does tool calling and thinking, and you should be able to explore pointing a coding harness at it if you turn on LM Studio or Unsloth Studio's API server. You could also use the Llama system tray app (formerly LlamaBarn) or just use llama-server from the llama.cpp distribution.
Probably Pi is going to be a better harness because it can have a minimal system prompt, though I've not tested it with Pi myself.
It seems to know PHP and SQL to a fairly decent depth (and I suspect JS and Python). It also has a unified vision model (it doesn't need a separate mmproj sidecar thingy) that is fairly fast, and it is quite impressive at image analysis.
So you could probably use it to generate image descriptions and tags, summarise text, generate wordpress snippets, that sort of thing.
It can capably answer questions like "Can you characterise this image and suggest further similar images I might like?" — I am currently using this to provoke me to take photos again.
Have a play with the E4B edge model, too — again, much more interesting than I expected.
dragonwritera month ago
The frontier is a multidimensional space defined by the “best” combination of traits a model can have in multiple dimensions: parameter size [smaller is better], various task metrics, and relative token generation speed on like hardware [faster is better], and active memory requirements [smaller is better] are all possible dimensions, and a model on the frontier of the current options space is one where getting better on one of those measures cannot be done without getting worse on at least one of the others.
zeckalphaa month ago
The frontier is a curve. https://en.wikipedia.org/wiki/Pareto_front
IshKebaba month ago
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.
barnabeea month ago
I’ve always seen the frontier shown as a curve on a plot. Frontier ≠ SOTA
zarzavata month ago
Frontier = SOTA.
Pareto frontier ≠ frontier.
chrisweeklya month ago
true but tfa's title says "frontier open models"
wmfa month ago
Frontier open models are Kimi K3, GLM 5.2, DeepSeek V4 Pro, etc. They're all too big to fit on most Macs.
andsoitisa month ago
> tfa's title says "frontier open models"
Does it? I read: "Run AI models locally on your Mac."
IshKebaba month ago
The submission is "Nativ: Run frontier open models locally on your Mac" and on the page it says "Nativ puts frontier intelligence on your desk."
andsoitisa month ago
> puts frontier intelligence on your desk
Which of the models it puts on your desk do you consider frontier intelligence?
IshKebaba month ago
None of them.
kube-systema month ago
That is one sense, but it is also use to refer to the frontier of capability. Especially in this context.
bnfcla month ago
Had the same though. The gap between open-source and the frontier is closing in, especially with Kimi K3, but that is like >2T parameters. The Gemma 4 and other models you can actually run on an average Mac, is not in the same league.
lucideera month ago
It might be overused elsewhere but I don't think its use here is inappropriate given it's qualified: it doesn't say "frontier models", it says "frontier open models".
jdthedisciplea month ago
No, your thinking is 100% correct. It's called clickbait.
44za12a month ago
+1 came here to say this, I opened the link expecting some technical breakthrough. Misleading click bait title.
D13Fda month ago
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.
moostiia month ago
LM studio is closed source software built ON TOP OF code released by the author of Nativ.
a3wa month ago
jan.ai is the F/LOSS alternative to it. If you do want a gui.
kzrdudea month ago
LM Studio seems to do the same thing, except that LM Studio is not open source. So they have a point, they do something more.
wmfa month ago
"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.
lylejohnsona month ago
I was wondering the same and assuming I'd overlooked something.
syntaxinga month ago
What spec is your macbook? I want to run Deepseek V4 Flash but its too slow for agents on my Strix Halo.
D13Fda month ago
It’s a maxed out current-gen MacBook Pro w/ 128gb ram. I lucked out in getting it before they upped the price.
It runs really well and fast enough for what I need, and it works great, but it’s slower than Claude. I use it for projects where I’m not allowed to use third party AI for legal reasons.
JosNuna month ago
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?
kgeista month ago
We've shipped some code generated by Qwen3.6 27B to production (under OpenCode). It lacks the breadth of knowledge of models like Opus, but if a change is fully inferable from the prompt and the surrounding code, it works very well. It won't be able to write something from scratch that requires niche knowledge (say, a performant inference engine tailored to Blackwell GPUs), but if it's just a PR adding a new use case to an existing project (which is usually just "load from the DB, do some invariant checks, modify the entities, store them back"), it works as well as Sonnet (provided you have the correct configuration, like recommended temperature and top-p settings, the model isn't over-quantized, you have at least 150k tokens of context available, etc.).
netghosta month ago
I don't use them as coding agents, but they can be very useful for things like text transformation, summarizing, or text extraction.
That said, if you have a subscription to a paid model already, you're not necessarily winning out on anything except perhaps privacy, which isn't nothing.
jiqirena month ago
there is plenty of grunt work these smaller models can do. update dependencies, fix merge conflicts, write --help, markdown, or readme files for existing code. etc.
sometimes they fail but undo is just a "git restore" or if automated, rejecting a PR and having a better model take a crack at it.
teaearlgraycolda month ago
They're great at helping me look up web dev stuff when I don't have internet access.
efficaxa month ago
I use a gemma4 model locally to extract content from messages to a personal agent I'm building for its memory graph (to break the message up into the topic, source (assistant or owner), facts, entities, etc. in the message content (all getting thrown into a magma-esque graph using NLEmbeddings for memory search). This is for a custom personal agent that targets deepseek-v4 flash. The local model is too slow in my setup for a chat agent, but for memory extraction it works pretty well, saving API usage on every chat turn.
mips_avatara month ago
Qwen35ba3b can do a huge amount of data cleaning work on pretty modest hardware. Already have run about 100 billion tokens on it using 2x3090 gpus.
febeda month ago
What exactly do you mean by data cleaning
mips_avatara month ago
The coolest project I’ve got this running on is improving the depicts metadata for photos on Wikipedia. A lot of times they won’t have the landmarks tagged correctly in a photo. So I will load in all the metadata that exists from each photo and the pixels of those photos and give a small qwen agent access to Wikipedia search as well as a geocoder. It does a great job of figuring out what is depicted and tagging it with the correct depicts field. Im still early on but I have been able to double the number of places that have a photo attached to them on wikimedia
febeda month ago
Interesting project. So I guess the search tool is to crawl Wikipedia for articles? And how do you ensure that the tagging stays within the Wikidata taxonomy? How exactly are you using a geocoder? Sorry, just curious
mips_avatara month ago
So like oftentimes the picture will be of a church and there’s geographic coordinates for where the photo was taken. My qwen will use the geocoder to search for “church” at the coordinates of the photo and then read the Wikipedia articles about all the churches nearby and see if any of them could plausibly be the church. So far I have parsed about 2 million photos and have tagged about 800k places. My goal is to do the whole 40 million places to create a world map of open places with photos. The tool I’m using is topoloop for the geocoding
nojaa month ago
are you using it differently to OpenRefine?
mips_avatara month ago
I’ve found it helps a lot with reconciliation tasks where tools like openrefine can’t handle it. Like I wanted to tag blog posts with links to Wikipedia articles that are relevant. But the thing is whats relevant changes a lot based on context in the blog post. So like a naive reconciler will tag the article for “sky” in the blogpost title “the sky above the Notre dame shone the morning we visited” when the element that should be tagged is the cathedral.
ActorNightlya month ago
[flagged]
invictatia month ago
Apple would not waste money astroturfing on HN to sell O(1000) Macs.
ActorNightly25 days ago
No, they would spend money on creating a trend, like "Macs are good for AI".
They literally did this before AI with Macs being good for programming, because "they are Unix like", "have the best trackpad" and other bullshit, and as a result, new CS grads were convinced that Macs are the best for programming.
kridsdale1a month ago
Wow what a hater. You know what else is thousands of dollars and doesn’t even include a monitor? An ATX case with 2 3090s in it. And that will use a kilowatt or more to do what the Studio (which is excellent) does with about 250 W.
ActorNightly25 days ago
Compute is compute. You need power to make LLMs go brrr.
And you can get a case with 2 3090s for about 5k, which is still less than what a "comparable" top of the line Mac Studio costs.
Nekorosua month ago
I really don't like the marketing texts. "Why we’re open source when nobody else is." I'm using oMLX which is open source and seems to be doing everything Nativ offers. I'd rather see the comparison with existing "non-existing" open source competitors.
giancarlostoroa month ago
What they likely mean is, why options like LM Studio are not open source.
kmike84a month ago
omlx is quite similar to LM Studio, so there are "options like LM Studio" which are open source
Daunka month ago
Is Gemma 4 E2B actually "usable"? I've been running Gemma 4 12B and it handles everything very well! But the second I've moved down to E4B it's been unable to perform the simplest of tasks. So I can't even imagine how E2B would do... Or am I doing something wrong?
shitcodera month ago
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
dofma month ago
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)
regexorcista month ago
Same here. Tried MLX twice at different times after reading the claims here but it always does considerably worse for me than llamacpp.
c4pt0ra month ago
I'm a bit curious why not running DeepSeek V4 on top of https://github.com/antirez/ds4. I think the results could be really good.
Archit3cha month ago
I assume Nativ doesn't support SSD streaming like DwarfStar.
satvikpendema month ago
Only interesting thing about this vibe coded runner is the MLX support, as that's still annoying to use in other ones, most still use GGUFs. Unsloth Studio which is an OSS runner I use is still in progress with MLX support although it's still a ways away.
jwra month ago
The word "frontier" is like "load-bearing" at this point (Claude Code users will know what I mean). I wish we could stop using it. Especially as this does not, in fact, run the leading/top models locally on your Mac.
rvza month ago
Looks like my call [0] for more competitors to Ollama has been answered.
We need more like this as well as llama.app, which also has a native mac app.
laughingcurvea month ago
Agreed. Just based on this not being Ollama, so I will give it a try.
0gsa month ago
my thing is kind of an Ollama competitor (surrogate?) too. more for prose/text planning, not so much for coding, at least the harness, but i'm sure someone could set it up to do that: github.com/0gsd/enough
diimdeepa month ago
I am still rocking Sequoia and this targets Tahoe purely from UI constraints, no like.
woadwarrior01a month ago
Ironic that the app is named Nativ(e) and yet bundles a full Python runtime. Nonetheless, still less bloated than LM Studio, which bundles a full Python runtime and electron.js (which in turn bundles a whole browser runtime).
bigyabaia month ago
A lot of macOS apps are statically-linked, even interpreted programs. It's still a native app for going that route.
isomorphica month ago
This looks like the Prism folks, who are making binary/ternary versions of popular edge models, so that those models will fit on constrained devices like phones. E.g., their Bonsai model derived from Qwen:
https://news.ycombinator.com/item?id=48910545
Perhaps they got tired of LM Studio, etc., not being able to run their models properly.
dofma month ago
Is it? The developer page for the github repo suggests he works at Arcee. Maybe he moved?
(I initially thought the same because of the website appearance)
shireboya month ago
What is the “middlest” Mac one could get for this? I’m in the market but keep going back and forth between a 64gb m5 pro or “lower end m5 air and screw it I’ll just pay for cloud tokens”. At current prices the 2-3k diff to try to run something local that isn’t as powerful could buy a lot of tokens.
froobiusa month ago
You can run a lot of these on e.g. M1 max 64gb
khursa month ago
Flagged this, as it is not 'frontier models' in the title of the linked page so not sure why has been titled that way here.
It's a further way to run mlx models
mlx are apple specific format for M3 or later CPUs, and some benchmarks show mlx are not always better than just running generic ones.
flyingcapabaraa month ago
If you are on Linux check out Box, it runs models locally , has img gen etc and many more features, I will be releasing the source soon just polishing out last bug's, help porting to other distributions is welcomed
Github.com/jegly/b0x
jsomedona month ago
I can't really tell why would I use this over like lm studio, jan.ai and such?
sajithdilshana month ago
Has anyone found a model that can run on a normal macbook? I have an M3 Pro with 18GB of memory and whenever I try to run even a basic model the fans goes off and the mac starts to get heated up and becomes so laggy.
mft_a month ago
There is a Gemma 4 model with 12B parameters which might be worth trying. e.g. https://huggingface.co/mlx-community/gemma-4-12B-it-qat-4bit
That said, your computer will still get hot!
Daunka month ago
I just run Gemma4 12B MLX via Ollama and it's been doing fantastic work!
kzrdudea month ago
If you go small enough it should be no problem. For example Gemma 4 E4B in Q6 or Q4 quantization should run well on your laptop. It shouldn't be too taxing, but would still want to eat 7-9 GB of VRAM or so.
Now that model is mostly useful for writing or chatting.
b3inga month ago
You need more RAM, plus the models take up a lot of space. 32gb min but I’d recommend 48/64gb, you won’t get close to frontier but it’s still fun to play with, images are very good
fl0ida month ago
heating up is normal, that cannot be avoided. it should become laggy, but you just have very little RAM (I assume 16 GB?) So most models are too big with other stuff running.
sixtyja month ago
Tbh, the only reason to run a model locally is when you want to be completely safe.
From productivity point of view, it doesn’t make sense to have any notebook running a local LLM.
We have one life. We should spend it wisely.
[deleted]a month agocollapsed
TechSquidTVa month ago
The server wont start for me. "ERROR: Application startup failed. Exiting." "mlx-vlm-server stopped with status 3"
saagarjhaa month ago
I'm a little confused why the page lists "UNIVERSAL · APPLE SILICON (M1+)". This seems like an oxymoron
jwra month ago
How is it better than, say, LM Studio? And does it run MTP models (which from what I understand are GGUF)?
SafeFatNooba month ago
so now we have this, https://pypi.org/project/rapid-mlx/, https://mtplx.com, and the oldest I could find at https://omlx.ai.
philipsa month ago
There is also https://github.com/ml-explore/mlx-swift-lm which is what https://jan.ai uses.
it25 days ago
I ran it with Qwen3-8B, and it responded to all input in the chat with
Could not connect to the server.
mfroa month ago
I don't love that this starts an API server on launch and has no option to disable it...
dlandisa month ago
Advice: remove all slop and fluff from the website such as "Everything you need. Nothing you don’t."
Just state the information you want to communicate in the plainest and most straightforward way possible.
sebmellena month ago
That phrase itself is such an astounding performative contradiction [0].
vitally3643a month ago
Something nobody needs is pointless hot air like "Everything you need. Nothing you don't."
thejazzmana month ago
You’d be surprised how hard this actually is. I spent 3 days iterating on a marketing site, where I had very explicit / “well written” copy, and it would just repeatedly rewrite it back to the most awful slop. Over and over again! Ended up adding various AGENTS rules telling it to leave the copy alone
jmpza month ago
Definitely easier and better than just writing the copy..
lantrya month ago
I think they're saying that they _had_ written the copy themselves, but were using the clanker for other tasks, and it kept going off course to "improve" the copy.
anentropica month ago
Try https://github.com/blader/humanizer agent skill
satvikpendema month ago
Just...write it yourself.
thejazzmana month ago
I did. And then it rewrote it. Over and over again. And I kept restoring it. And it kept taking agency to change it to some other neutral slop.
That’s the point.
para_parolua month ago
I don’t think anyone ever looked at result. Website if full of overflow bugs. It’s pure slop.
sajithdilshana month ago
true, it doesn't render properly on mobile. Although I quite like the design. It's a new AI design guide (font/color choice) I haven't seen in in other AI designed pages
m3kw9a month ago
The site design itself is likely one shotted. The italic fonts is nauseating
[deleted]a month agocollapsed
nojaa month ago
Can you add support to download gated models?
jarek83a month ago
Ok, so we're at the point that even design are just one-shot by AI. This is exact look and feel any time I ask it to present a HTML doc about anything.
moostiia month ago
The webpage isn't the point. The software the webpage refers to is the point.
cootsnucka month ago
So should I ditch ollama for this?
n8henriea month ago
Any reason to use this over omlx?
reaglea month ago
That's what I wondered.
themihaia month ago
What’s the BS with “Open models from teams we trust.”?
VaporJournalAPPa month ago
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troygentica month ago
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Atlas_Smitha month ago
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troygentica month ago
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audioh4ckera month ago
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flyingcapabaraa month ago
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brcmthrowawaya month ago
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przemarzeca month ago
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iAMkenougha month ago
How does this compare to LM Studio Bionic?
asqueellaa month ago
Bionic is an agent; this appears to be an open-source competitor to lmstudio. The initial commit is just a few hours ago though, so …
calumcla month ago
The maintainer works on mlx-vlm so he does have pedigree in the scene, I'm don't know if this is just going to end up as unmaintained slop. I haven't tried this but I would personally just recommend oMLX for a currently more complete and fleshed out package - loads of features, provides the same MLX support and changelogs + commits are actually detailed.
jdiffa month ago
I use oMLX and I'm tentatively going to be giving this a shot. oMLX keeps driving me up a wall with odd papercuts, bugs, and silent failures and fallbacks that are only visible buried deep inside logs when they should be announced out loud.
The maintainer of mlx-vlm being behind this as well is the main thing kicking me over into trying it, even if it is incredibly young. I'm confused and unenthused to see it chomping on a whole GB of disk, but the Swift makes it feel much more refined even if it's not yet as feature rich. It automatically picked up the existing models I was using with mlx_vm directly, which was nifty.
crefiza month ago
Why do ppl downvote this comment? HN makes no sense sometimes...