Raspberry Pi's New AI Hat Adds 8GB of RAM for Local LLMs

https://www.jeffgeerling.com/blog/2026/raspberry-pi-ai-hat-2/

by ingve • 6 months ago

256 209 6 months ago

jeffgeerling.com

dwedge• 6 months ago

In practice, it's not as amazing as it sounds.

8GB RAM for AI on a Pi sounds underwhelming even from the headline

agent013• 6 months ago

A good illustration of how “can run LLM” ≠ “makes sense to run LLM”. A prime example of how numbers in specs don’t translate into real UX.

phito• 6 months ago

Sounds like some PM just wanted to shove AI marketing where it doesn't make sense.

buran772• 6 months ago

I think Raspberry lost the magic of the older Pis, they lost that sense of purpose. They basically created a niche with the first Pis, now they're just jumping into segments that others created and are already filled to the brim with perhaps even more qualified competition.

Are they seeing a worthwhile niche for the tinkerers (or businesses?) who want to run local LLMs with middling performance but still need full set of GPIOs in a small package? Maybe. But maybe this is just Raspberry jumping on the bandwagon.

I don't blame them for looking to expand into new segments, the business needs to survive. But these efforts just look a bit aimless to me. I "blame" them for not having another "Raspberry Pi moment".

P.S. I can maybe see Frigate and similar solutions driving the adoption for these, like they boosted Coral TPU sales. Not sure if that's enough of a push to make it successful. The hat just doesn't have any of the unique value proposition that kickstarted the Raspberry wave.

ulnarkressty• 6 months ago

That niche was long taken over by cheap Chinese SBCs, so they have to innovate somehow. Their only advantage that remains is the community.

mschuster91• 6 months ago

The thing with the Chinese SBCs is that (like every other player in the embedded world) they don't give a flying fuck about upstreaming their code to the Linux kernel.

Of course, Raspberry Pi just like everyone else has their custom patches, but at least to my knowledge you can use a straight Linux kernel and still have a running system.

joe_mamba11• 6 months ago

Yep. RPi foundation lost the plot a long time ago. The original RPi was in a league of its own when it launched since nothing like it existed and it was cheap.

But now if I want some low power linux PC replacement with display output, for the price of the latest RPi 5, I can buy on the used market a ~2018 laptop with a 15W quad core CPU, 8GB RAM, 256 NVME and 1080p IPS display, that's orders of magnitude more capable. And if I want a battery powered embedded ARM device for GPIO over WIFI, I can get an ESP32 clone, that's orders of magnitude cheaper.

Now RPi at sticker price is only good for commercial users since it's still cheaper than the dedicated industrial embedded boards, which I think is the new market the RPI company caters to. I haven't seen any embedded product company that hasn't incorporate RPis in its products they ship, or at least in their lab/dev/testing stage, so if you can sell your entire production stock to industrial users who will pay top dollar, why bother making less money selling to consumers, just thank them for all the fish. Jensen Huang would approve.

haunter• 6 months ago

Not just laptops but the used enterprise micro PCs from Dell, HP, and Lenovo. All the same small form factor with very low TDP You can have up to 32 or 64 GB RAMs depending on the CPU, dual or even triple disks if you want a NAS etc.

qsera7• 6 months ago

I can buy on the used market a ~2018 laptop with a 15W quad core CPU, 8GB RAM, 256 NVME and 1080p IPS display, that's orders of magnitude more capable..

But it won't be as reliable, mostly motherboards won't last long.

Mashimo11• 6 months ago

I still use Pis in my 3d printers. Laptop would be too big, and a ESP could not run the software. "China clone" might work, but the nice part of the pi is the images available. It just works™

I'm also currently building a small device with 5" touchscreen that can control a midi fx padle of mine. It's just so easy to find images, code and documentation on how to use the GPIO pins.

Might be niche, but that is just what the Pi excels at. It's a board for tinkers and it works.

cyberax3• 6 months ago

RPi will still have lower power consumption and is far more compact. And mechanically reliable.

I'm in the market to replace my aging Intel NUCs, but RPi is still cheaper.

u8080• 6 months ago

There are also N100/N150 SBC offers which are superior to RPi

systemtest3• 6 months ago

In The Netherlands the first generation RPi was only sold to users with a Chambers of Commerce registration, I figured this was always the typical end user for it. Like schools, universities, prototyping for companies. Was the RPi in the rest of the world targeted towards home users?

* https://tweakers.net/nieuws/80350/verkoop-goedkoop-arm-syste...

pipes• 6 months ago

I'd love to buy a 500+

https://www.raspberrypi.com/products/raspberry-pi-500-plus/

I can't justify it though as I've no use for it.

However I think it is way closer to their original vision than anything else, i.e. It is a lot like the 1980s computers, the magic they were trying to capture.

theshrike795• 6 months ago

I had just gotten into Arduinos when the first Raspberry Pi came out.

I noticed I can do 90% of the stuff I'd use an Arduino for with a RPi, except I had the full power of an internet connected Linux machine available. The Arduinos are still collecting dust somewhere =)

But now we have the ESP32 filling the same niche along with the Pi Zero W, so I don't really understand the purpose of RPi 4 and 5. They're not cheap compared to the price nor very powerful in any measure.

You don't even need a full laptop, any Chinese miniPC will blow the RPi5 out of the water AND some of them have expandable storage+RAM, while also having 5-20x more CPU/GPU oomph. They do consume a few watts more power, so there _might_ be a niche for the Raspberry Pi, but it's not a big one.

worldsavior• 6 months ago

RPi supporting Linux is already a big benefit. Using a laptop with a battery isn't very convenient and dangerous (always being charged).

TazeTSchnitzel• 6 months ago

The Raspberry Pi probably still has the advantage of an actually robust firmware/software ecosystem? The problem with SBCs has always been that the software situation is awful. That was the Raspberry Pi's real innovation: Raspbian and a commitment to openness.

vachina• 6 months ago

The problem with SBCs has always been that the software situation is awful

Awful how? A SBC can take advantage of many software written from the dawn of x86.

cbm-vic-20• 6 months ago

Fragmentation in the non-x86 world really hurts adoption. RPi presents a very well documented configuration that can be used as a target for development.

RISC-V is going through this exact same problem right now. All of the current implementations have terrible documentation, and tailoring Linux for each of these is proving to be difficult. All of these vendors include on-board devices that have terrible doc and software support.

crimsoneer• 6 months ago

Not everything needs to be for everyone. I think this is super cool - I run a local transcription tool on my laptop, and the idea of miniaturising it is super cool.

noodletheworld2• 6 months ago

It is neat, and at 32GB it might be useful.

Almost nothing useful runs in 8.

This is the problem with this gen of “external AI boards” floating around. 8, 16, even 24 is not really enough to run much useful, and even then (ie. offloading to disk) they're so impractically slow.

Forget running a serious foundation model, or any kind of realtime thing.

The blunt reality is fast high memory GPU systems you actually need to self host are really really expensive.

These devices are more optics and dreams (“itd be great if…”) than practical hacker toys.

buran772• 6 months ago

Not everything needs to be for everyone

I wouldn't dare suggest that. The RPi was never for everyone yet it turned out it was for many. It was small but powerful for the size, it was low power, it was extremely flexible, it had great software support, and last but not least, it was dirt cheap. There was nothing like that on the market.

They need to target a "minimum viable audience" with a unique value proposition otherwise they'll just Rube-Goldberg themselves into irrelevance. This hat is a convoluted way to change the parameters of an existing compromise and turn it into a different but equally difficult compromise. Worse performance, better efficiency, adds cost, and it doesn't differentiate itself from the competing Hailo-10H-based products that work with any system not just RPi (e.g. ASUS UGen300 USB AI Accelerator).

the idea of miniaturising

If you aren't ditching the laptop you aren't miniaturizing, just splitting into discrete specialized components.

dev_l1x_be• 6 months ago

I love RPI4s for local homelab roles like DNS servers, even for NAS with USB attached external storage, VPN gateways (with Tailscale).

baq2• 6 months ago

It's actually not great since Ethernet is over USB on the pi 4 (edit this is not true, confused with pi 3). Not that it doesn't work, but I'd rather have an N100 minipc.

OTOH with ram prices being where they are and no signs of coming back down in the foreseeable future a second hand pi 4 may be a very wise choice.

oliwarner• 6 months ago

Nah, they released products better suited to what people were already using Pis for.

The Picos are great for the smaller stuff, new Pis are great for bigger stuff, and old Pis and Zeros are still available. They've innovated around their segment.

The AI stuff is just an expression of that. People are doing AI on Pi5s and this is just a way to make that better.

avhception5• 6 months ago

I don't know of any other ARM device that fulfills:

- I can boot it w/o having to learn about custom U-Boot implementations

- I, as a consumer or small business, can buy

- Can not only buy today but also still buy in 2 years

- Doesn't cost a small fortune

- Can be tugged away behind TVs and other small niches

muggesmuds• 6 months ago

Odroids!

dominicrose• 6 months ago

I understand wanting to run a local LLM for privacy, but on something more powerful. Yes it's costly but what use is an LLM on a cheap board?

wpm• 6 months ago

Why does it need to be ARM?

theshrike795• 6 months ago

Not ARM, but:

https://www.gmktec.com/products/nucbox-g3-plus-enhanced-perf...

If ARM is a requirement, then RPi is your only option that I know of.

pibaker3• 6 months ago

Whenever the Pi gets brought up people on HN will tell you you are wasting money if you are not buying a Chinese Pi clone with beefier specs instead. But at least for me, "Being able to boot into a Linux system without having to dig through outdated wikis and Chinese language support forums to hunt down a google drive link to an OS image from 2021 that has since then received zero updates" is definitely worth paying ten extra dollars for.

ajsnigrutin• 6 months ago

You don't need an ARM, and for the same price, before the RAM crisis, you could get many tiny PCs for the same amount of money, with proper SSDs and power supplies and in tiny form factors.

https://teampandory.com/2024/09/24/gmktec-g5-mini-pc-review-...

Something like this ($155) cost less than the Pi + case + power supply + nvme addon board + ssd, and it also runs windows and any other x86 OS.

Croak3• 6 months ago

People have for quite some time been using Googles Tensor chip to accelerate AI workloads on the Pi. I doubt that anyone runs Llms on Pis but stuff like security cameras with object detection...

nirav722• 6 months ago

I read somewhere that Google has largely abandoned support for their Coral TPUs? I still use a Coral TPU for Frigate NVR. But not sure how long they'll be supported.

mindcrash2• 6 months ago

I think Raspberry lost the magic of the older Pis, they lost that sense of purpose. They basically created a niche with the first Pis, now they're just jumping into segments that others created and are already filled to the brim with perhaps even more qualified competition.

I don't think you will find anything on the market enabling you to create your own audiophile quality AMP, DAC, or AMP+DAC for a pretty attractive price except a Pi 3/4/5 with a HifiBerry (https://www.hifiberry.com/) HAT.

yoavm2• 6 months ago

There are some nice ESP-based solutions - https://sonocotta.com/esp-products/

NoboruWataya• 6 months ago

IMO this is a consequence of Raspberry Pi going for-profit and IPOing. Now they are incentivised to chase the same hype trains as every other public tech company. I can't see them having another "Raspberry Pi moment", those are too risky now.

That said, more options at the (relatively speaking) low end of the AI hardware market probably isn't a bad thing. I'm not particularly an AI enthusiast generally, but if it is going to infest everything anyway, then at least I would like a decent ecosystem for running local models.

windexh8er• 6 months ago

I think this is a miss on what the Pi is: an experiment. Sure, it stood on the shoulders of other SFF boards that came before it - but it broke into the general computing landscape targeting makers and builders. If the AI hat doesn't work out, so be it. The use cases for this type of hat may yet to be seen. On one hand it may feel shortsighted to bringing hardware to market with no explicit use case, but that's part of the Pi brand.

As someone else mentioned: if the hat could efficiently be leveraged with the YOLO models on Frigate for a low volume camera setup that could be a nice niche use case for it.

Either way I hope the RPi org keeps dropping things like this and letting the users sort out the use cases with their dollars.

ChromaticPanic3• 6 months ago

On device processing for robots and drones

Zetaphor2• 6 months ago

Everyone here is missing the fact that this board was made by a third party, not the Raspberry Pi organization.

rocketvole2• 6 months ago

What? Sure, its technically using technology by hailo, but it's definitely from the RPI organization

jasongill• 6 months ago

It's not "made by a third party" - it's sold as a first-party add-on, by Raspberry Pi on their own website, in a Raspberry Pi branded package.

https://www.raspberrypi.com/products/ai-hat-plus-2/

It's no more "made by a third party" than any other electronics device made by a contract manufacturer.

lenerdenator• 6 months ago

Gotta get that investor cash.

In regard to their niche, their niche is a ridiculously well-documented ecosystem for SBCs. Want to do something with your RPi? You can find it on Google, and the LLM of your choice is probably trained to give you the answer on how to do it. If you're just tinkering or getting a POC ready, that's a big help.

Of course, if you're in the business of hardware prototyping, and have a set of libraries and programs you know you're going to work with, you don't need to care as much.

andix• 6 months ago

My biggest issue is the lack of really good cases. There are all those fancy peripherals you can buy, but it's really hard to find simple case that works without overheating and no cables sticking out on all four sides.

nkko• 6 months ago

That magic now moved to ESP32.

rpcope1• 6 months ago

This is why I keep buying 3B+ and Zero 2 W and not any of the newer versions...it's much more in keeping with the relatively low cost board with GPIO and reasonable compute. It's kind of the last one they made that does what I kind of expected out of a Raspberry Pi at a reasonable price point. If I needed more compute I would have skipped the travesty that is ARM and just bought an x86 system.

iamrobertismo3• 6 months ago

I feel like if RPI doubled down heavily into education, they would be in a much better spot. They really could never win on price in the long run. But having a bit of K-12 and university budgets going to RPIs every year, especially during the "teach the kids programming" era, would I think make them a much healthier business.

Chromebooks did what RPI should have done.

alnwlsn• 6 months ago

I still remember the email I got telling me that they were going to upgrade the RAM of the 256Mb Model B I ordered and that I would receive a brand new model with 512Mb for no extra cost. Hard to believe that was nearly 14 years ago.

Was very helpful in me learning Linux. The only alternative I had at the time was a few old Pentium 4 machines, which were very noisy and my parents didn't like me leaving turned on for a long time.

0xbadcafebee• 6 months ago

The original Pis are still for sale, are cheap, and still do everything you need. This doesn't conflict with an expanded product line. The whole reason for Pi is still GPIO plus general purpose computing. AI is now a part of general purpose computing, so it only makes sense to adopt it too.

The things you can do locally with AI now are amazing. For several years there's been multiple open source products that can do both audio and visual processing locally using AI models. Local-only Home Assistant is almost equivalent to Siri. The more things you throw at it, the more computing power it needs (especially for low latency), and that's where the dedicated GPUs/NPUs (previously ASICs) are needed. And consider the expanded use cases; drones and robots can now navigate the world autonomously using a $150 SoC and some software.

atmosx• 6 months ago

Do sales backup these claims that come up very often or not? Does anyone has any data?

Although the op is not wrong, maybe their decisions are data driven and pay off?

turtlebits• 6 months ago

May have lost the magic with regards to price, but they're commodity hardware now.

My rpi3 (that's been running since 2019) died last year and I was able to buy another and just plug in the SD card.

moffkalast• 6 months ago

The Pi's built-in CPU trounces the Hailo 10H.

Case closed. And that's extremely slow to begin with, the Pi 5 only gets what, a 32 bit bus? Laughable performance for a purpose built ASIC that costs more than the Pi itself.

In my testing, Hailo's hailo-rpi5-examples were not yet updated for this new HAT, and even if I specified the Hailo 10H manually, model files would not load

Laughable levels of support too.

As another datapoint, I've recently managed to get the 8L working natively on Ubuntu 24 with ROS, but only after significant shenanigans involving recompiling the kernel module and building their library for python 3.12 that Hailo for some reason does not provide outside 3.11. They only support the Pi OS (like anyone would use that in prod) and even that is very spotty. Like, why would you not target the most popular robotics distro for an AI accelerator? Who else is gonna buy these things exactly?

renewiltord• 6 months ago

What’s the current state of the art in low power wake word and speech to text? Has anyone written a blog post on this?

I was able to run a speech to text on my old Pixel 4 but it’s a bit flaky (the background process loses the audio device occasionally). I just want to take some wake word and then send everything to remote LLM and then get back text that I do TTS on.

geerlingguy2• 6 months ago

Maybe not SOTA but the HA Voice Preview Edition [1] in tandem with a Pi 5 or some similar low-power host for the Piper / Whisper pipeline is pretty good. I don't use it but was able to get an Alexa/Google Home-like experience going with minimal effort.

I was only using it for local Home Assistant tasks, didn't try anything further like retrieving sports scores, managing TODO lists, or anything like that.

[1] https://www.home-assistant.io/voice-pe/

monocasa• 6 months ago

Wake word can be tiny. Like 10k weights and can run on an esp32 or similar with plenty of compute to spare.

TinyML is a book that goes through the process of building a wake word model for such constrained environments.

folmar• 6 months ago

Wake word is not expensive, you can do it on esp32 https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3... (and then send audio to something more beefy as TTS will be marginal at best).

huntercaron• 6 months ago

Glad Jeff was critical here they need a bit of a wake up call it seems.

speedgoose• 6 months ago

Is there any usefulness with the small large language models, outside perhaps embeddings and learning?

I fail to see the use-case on a Pi. For learning you can have access to much better hardware for cheaper. Perhaps you can use it as a slow and expensive embedding machine, but why?

kouteiheika• 6 months ago

A natural language based smart home interface, perhaps?

Tiny LLMs are pretty much useless as general purpose workhorses, but where they shine is when you finetune them for a very specific application.

(In general this is applicable across the board, where if you have a single, specific usecase and can prepare appropriate training data, then you can often fine-tune a smaller model to match the performance of a general purpose model that is 10x its size.)

michaelmior• 6 months ago

I think there's a lot of room to push this further. Of course there are LLMs being used for this case and I guess it's nice to be able to ask your house who the candidates were in the Venezuelan presidential election of 1936, but I'd be happy if I could just consistently control devices locally and a small language model definitely makes that easier.

cmpxchg8b• 6 months ago

8GB? What is this, an LLM for ants?

matja• 6 months ago

It's more about demonstrating what's possible on a Pi than expecting GPT-4 level performance. It's designed for LLMs that specialize in tiny, incredibly specific tasks. Like, "What's the weather in my ant farm?" ;)

The vision processing boost is notable, but not enough to justify the price over existing HATs. The lack of reliable mixed-mode functionality and sparse software support are significant red flags.

(This reply generated by an LLM smaller than 8GB, for ants, using the article and comment as context).

kirurik• 6 months ago

You can run some models pretty decently using CPU inference only, things like Gemma 3 that are built for exactly that use case or some tiny speech to text models via llama.cpp that I have tested out (not so good). Although not the best for "heavy" tasks, if you just need a decent text generator that can produce more or less sensible, generic output you are good to go.

kotaKat• 6 months ago

"For example, the Hailo 10H is advertised as being used for a Fujitsu demo of automatic shrink detection for a self-checkout."

... why though? CV in software is good enough for this application and we've already been doing it forever (see also: Everseen). Now we're just wasting silicon.

Barathkanna• 6 months ago

As an edge computing enthusiast, this feels like a meaningful leap for the Raspberry Pi ecosystem. Having a low-power inference accelerator baked into the platform opens up a lot of practical local AI use cases without dragging in the cloud. It’s still early, but this is the right direction for real edge workloads.

saagarjha• 6 months ago

Which ones?

Croak3• 6 months ago

For example camera based object detection. People have been using usb Dongel Google Tensors for that previously

Croak3• 6 months ago

For example camera based object detection. People have been using usb Dongel Google Tensors for that previously.

lopis• 6 months ago

A smarter home assistant would be one

teekert• 6 months ago

At this moment my two questions for these things are:

1. Can I run a local LLM that allows me to control Home Assistant with natural language? Some basic stuff like timers, to do/shopping lists etc would be nice etc.

2. Can I run object/person detection on local video streams?

I want some AI stuff, but I want it local.

Looks like the answer for this one is: Meh. It can do point 2, but it's not the best option.

worksonmine• 6 months ago

1. Probably, but not efficiently. But I'm just guessing I haven't tried local LLMs yet.

2. Has been possible in realtime since the first camera was released and has most likely improved since. I did this years ago on the pi zero and it was surprisingly good.

noodletheworld2• 6 months ago

Can I run a local LLM that allows me to control Home Assistant with natural language? Some basic stuff like timers, to do/shopping lists etc would be nice etc.

No. Get the larger PI recommended by the article.

Quote from the article:

So power holds it back, but the 8 gigs of RAM holds back the LLM use case (vs just running on the Pi's CPU) the most. The Pi 5 can be bought in up to a 16 GB configuration. That's as much as you get in decent consumer graphics cards1.
Because of that, many quantized medium-size models target 10-12 GB of RAM usage (leaving space for context, which eats up another 2+ GB of RAM).

…

8 GB of RAM is useful, but it's not quite enough to give this HAT an advantage over just paying for the bigger 16GB Pi with more RAM, which will be more flexible and run models faster.

The model specs shown for this device in the article are small, and not fit for purpose even for the relatively trivial use case you mentioned.

I mean, look, lots of people have lots of opinions about this (many of them wrong); it’s cheap, you can buy one and try… but, look. The OP really gave it a shot, and results were kind of shit. The article is pretty clear.

Don’t bother.

You want a device with more memory to mess around with for what you want to do.

rballpug• 6 months ago

Catalog TG 211, 1000 Hz.

endymion-light3• 6 months ago

can't wait to not be able to buy it, and also for it to be more expensive than a mini-computer

I buy a raspberry pi because I need a small workhorse - I understand adding RAM for local LLMs, but it would be like a raspberry pi with a GPU, why do i need it when a normal mini machine will have more ram, more compute capacity and better specs for cheaper?

rocketvole2• 6 months ago

a lot of people buy rpis because they are the only reasonable option for connectivity with power. I'm not sure what other devices you can get that have gpio and mipi connectivity with the ability to (potentially) run vlms and llms on them.

I daresay they could charge more than a comparably specced computer (if they don't already) and they would still be a viable purchase.

endymion-light3• 6 months ago

Surely with this hat you don't have any access to any GPIO?

Unless i'm missing something - which is where i'm like why not just buy a NUC with similiar RAM for far less.

t43562• 6 months ago

In the UK I've never seen the hailo hats (which are quite old BTW) advertised for LLMs. The presented usecase has been object detection from lots of video cameras in realtime.

They seem very fast and I certainly want to use that kind of thing in my house and garden - spotting when foxes and cats arrive and dig up my compost pit, or if people come over when I'm away to water the plants etc.

[edit: I've just seen the updated version in Pimonori and it does claim usefulness for LLMs but also for VLMs and I suspect this is the best way to use it].

esskay• 6 months ago

What a pointless product to waste time making.

joelthelion• 6 months ago

8GB is really low.

That said, perhaps there is a niche for slow LLM inference for non-interactive use.

For example, if you use LLMs to triage your emails in the background, you don't care about latency. You just need the throughput to be high enough to handle the load.

wyldfire2• 6 months ago

I wonder -- how does this thing compare against the Rubik Pi [1]?

[1] https://rubikpi.ai/

philipallstar• 6 months ago

Is that affiliated with raspberry pis in some way, or are they just freeloading on the "pi" suffix to confuse people?

Elfener• 6 months ago

are they just freeloading on the "pi" suffix to confuse people?

Yes, but that is normal I guess:

- https://banana-pi.org/

- http://www.orangepi.org/index.html

- https://radxa.com/products/rockpi

wyldfire2• 6 months ago

They are "freeloading" indeed but in this case it is a valuable indicator that it should be physically compatible with many add-ons/attachments that are compatible with the Raspberry Pi.

imtringued• 6 months ago

This looks pretty nice for what it is. However, the RAM is a bit oversized for the vast majority of applications that will run on this, which is giving a misleading impression of what it is useful for.

I once tried to run a segmentation model based on a vision transformer on a PC and that model used somewhere around 1 GB for the parameters and several gigabytes for the KV cache and it was almost entirely compute bound. You couldn't run that type of model on previous AI accelerators because they only supported model sizes in the megabytes range.

Lio• 6 months ago

I've seen the AI-8850 LLM Acceleration M.2 Module advertised as an alternative RPi accellorator (you need an M.2 hat for it).

That's also limited to 8Gb RAM so again you might be better off with a larger 16Gb Pi and using the CPU but at least the space is heating up.

With a lot of this stuff it seems to come down to how good the software support is. Raspberry Pis generally beat everything else for that.

Havoc• 6 months ago

That seems completely and utterly pointless.

A NPU that adds to price but underperforms a rasp cpu?

You get SBC with 32gb ram…

Nevermind the whole minipc ecosystem which will crush this

nottorp• 6 months ago

Hmm. Can this "AI" hardware - or any other "AI" hardware that isn't a GPU - be used for anything other than LLMs?

YOLO for example.

dismalpedigree• 6 months ago

Yes. The Hailo chips are mainly for AI vision models. This is the first time I have seen them pushed for LLM. They are very finicky and difficult to setup outside of the examples. Documentation is inconsistent and the models have to be converted to a different format to run. It is possible to run a custom yolo8 model, but is challenging.

_ea1k• 6 months ago

I'd expect that kind of thing to be the primary use case, tbh. Maybe even running whisper models?

If it could run whisper, it'd be a solid addition to a pi based home assistant setup.

vander_elst• 6 months ago

I had a couple of Pis that I wanted to use as a Media center, I always had some small issues that created a suboptimal experience. Went for a regular 2nd hand amd64 with a small form factor and never looked back, much better userspace support and for my use case a much smoother experience, no lags no memory swapping and if needed I can just buy a different memory bank or a different component. I have no plans to use a raspberry pi any time soon. I am not sure these days if they really still have a niche to fill and if yes how large this niche is.

JustFinishedBSG• 6 months ago

It's useless for LLMs and it's actually slower than Hailo 8H for standard vision tasks, so, why ?

myrmidon• 6 months ago

Are there significant usecases for the really small LLMs right now (<10b distills and such)?

My impression so far was that the resulting models are unusably stupid, but maybe there are some specific tasks where they still perform acceptably?

arkmm• 6 months ago

They're still very good for finetuned classification, often 10-100x cheaper to run at similar or higher accuracy as a large model - but I think most people just prompt the large model unless they have high volume needs or need to self host.

syntaxing• 6 months ago

Interesting idea. I think the Jetson Orin Nano is a better purchase for this application. The main downside is the RAM is shared so you lose about 1G from the OS overhead.

giantg22• 6 months ago

What not use a USB Coral TPU? Seems to do mostly the same stuff and is half the price.

geerlingguy2• 6 months ago

Coral is many times slower at this point (2 TOPS IIRC), but if it meets your needs, it's okay.

giantg22• 6 months ago

Yeah, I think it's 4 TOPS, so I see.

incomingpain• 6 months ago

I wonder if this is the magic hardware for LiquidAI/LFM2.5-Audio-1.5B

Dont need more than 8gb. It'll be enough power. IT can do audio to audio.

djhworld• 6 months ago

A few years ago this product would have just been called an ML Accelerator and marketed as helping accelerate ML workloads like object detection in images

Hitching their wagon to the AI train comes with different expectations, leading to a mixed bag of reviews like this.

yawniek• 6 months ago

i wonder how the Hailo 10H compares to Axera AX8850. add on boards seem to be cheaper and its a full SoC that can also draw much more power.

yjftsjthsd-h• 6 months ago

Any chance you can split layers so that some run on the CPU and some run on this board to let you run bigger models and/or get better performance?

xp84• 6 months ago

Gigabytes?? In THIS economy?

1970-01-01• 6 months ago

It does seem like this is a marketing gimmick. I doubt it will have worked in terms of sales numbers. "What else does it do?"

venturecruelty• 6 months ago

Are computers even for anything else anymore? Is it just AI until the bubble pops? This is exhausting.

janalsncm• 6 months ago

Excited to see more hardware competition at this level. Models that can run on this amount of RAM are right in the sweet spot of small enough to train on consumer-grade GPUs (e.g. 4090) but big enough to do something interesting (simple audio/video/text processing).

The price point is still a little high for most tasks but I’m sure that will come down.

rootusrootus• 6 months ago

Within minutes of each other I can read a bunch of comments about how an 8GB AI hat for RPi would be grand for LLMs, while another contingent points out that my M2 MAX 96GB MacBook is completely useless for LLMs. All I can say is at least the latter is also a great laptop.

bigyabai• 6 months ago

For server use, the Pi is cheaper, better-supported and lower power. I really cannot recommend that anyone spend $2,500+ to run inference on a laptop that is slower than $300 GPUs.

sxzygz• 6 months ago

My primary concern with this offering is vendor of the enabling silicon. I think it’s important to consider who you do business with. The industrial uptake of RPi boards has poisoned their mandate and made them forget making a world where all children can discover the magic of computing, not just the special chosen ones.

tonymet• 6 months ago

Can someone share a non-theoretical LLM application that demands local inference and pocketable hardware? The internet hype for these is sky high, but the actual results are disappointing.

5ersi• 6 months ago

This AI 8GB HAT is $150, while better performing Pi5 8GB is $100. Makes no sense to buy the AI HAT.

bdavbdav2• 6 months ago

Have we not all given up on pis at this stage? I’ve got ESP32s for edge I/O, Nucs/VMs for the crunch. What’s the Pi doing?

scq• 6 months ago

There are definitely use cases. Pis have lower power consumption than NUCs. This is the main reason I went for one to run Home Assistant rather than a NUC.

I have a NAS/home server that I could put it on but I don't want my home automation going down when I tinker with it.

bdavbdav2• 6 months ago

I think I’ve got too used to VM snapshotting to turn away from it for HA.

Western0• 6 months ago

can You add gemma 3n to benchmark? this is less tahan normal 3 gemma but still good in small memory

Raspberry Pi's New AI Hat Adds 8GB of RAM for Local LLMs

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