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.
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.
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.
How much cheaper then 50 bucks can a tablet get? With the pi I can quickly in a hacky way connect rotary encoders with female-female dupon cables, use a python GPIO library made for raspberry pi.
https://media.discordapp.net/attachments/1461079634354639132...
I can also use it for Zynthian. And if I'm done with it, I can build a new printer :P
It's 10 bucks more. ¯\_(ツ)_/¯ Still half the price that I see intel NUCs for sale. Which of course are way more capable. But still, I don't mind the price that much.
I could go with a cheaper alternative, but then AFAIK you might have to fiddle with images, kernel and documentation. For me that is worth 10 bucks.
I don't really care how it compares to past models or inflation to justify its price tag. I was just comparing to to what you can buy on the used market today for the same price and it gets absolutely dunked on in the value proposition by notebooks since the modern full spec RPi is designed to more of a ARM PC than an cheap embedded board.
60 Euros for 2GB and 100 for 8GB models is kind of a ripoff if you don't really need it for a specific niche use case.
I think an updated Pi-zero with 2GB RAM and better CPU stripped of other bells and whistles for 30 Euros max, would be amazing value, and more back to the original roots of cheap and simple server/embedded board that made the first pi sell well.
The mobile and embedded X86 chips have closed the gap a lot in power consumption since the PI first launched.
Now you can even get laptops with broken screens for free, and just use their motherboard as a home server alternative to a PI. Power consumption will be a bit higher, but not enough to offset the money you just saved anytime soon.
https://www.insidemylaptop.com/wp-content/uploads/2018/03/Le...
The big pain with using something like this would mostly be the IO and odd form factor.
What prices are you using for the 3b and 5 to get this percentage? The lowest percentage I got from available data is a 57% increase ($35 -> $55)
40 EUR form 2016 is now ~52 EUR.
Compared to 62 EUR for the current model.
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.
And the thin clients when they are for sale tend to have their SSDs ripped out by IT for data security, so then it's a hassle to go out and buy and extra SSD, compared to just buying a used laptop that already comes with display , keyboard, etc.
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.
For 100€ that would be something I'd buy for every niece and nephew to play with. For 200€ it's not even for me, I'd rather buy something like the uConsole RPI-CM4: https://www.clockworkpi.com/product-page/uconsole-kit-rpi-cm...
* https://tweakers.net/nieuws/80350/verkoop-goedkoop-arm-syste...
I'm in the market to replace my aging Intel NUCs, but RPi is still cheaper.
I don't think I could a RPi as cheaply once parts and power supply etc are taken into account.
What moving parts do competitors have to be less mechanically reliable?
In fact, a NUC or used laptop would be even more reliable since you can replace NVME storage and RAM sticks. If your RPI ram goes bad you're shit out of luck.
>RPi will still have lower power consumption and is far more compact.
Not that big of on an issue in most home user cases as a home server, emulator or PC replacement. For industrial users where space, power usage and heat is limited, definitely.
>I'm in the market to replace my aging Intel NUCs, but RPi is still cheaper.
Cheaper if you ignore much lower performance and versatility vs a X86_X64 NUC as a home server.
> Not that big of on an issue in most home user cases as a home server
I don't know what "most home users" want, but I can understand wanting something more compact and efficient (also easier to keep cool in tighter or closed spaces), even at home.
> Cheaper if you ignore much lower performance and versatility vs a X86_X64 NUC as a home server.
Or maybe they noticed they don't need all the performance and versatility. Been there. It's plenty versatile and can run everything I need.
There are dozens and dozens of NUC style / form factor machines available these days. Especially cheap ones from China. Not sure what you mean by gaping hole post 2023. I'm running 3 of them with N97 and N150 Cpus. All bought within the last 18 months.
But it won't be as reliable, mostly motherboards won't last long.
The ticking timebomb lemons with reliability or design issues, will just die in the first 2-4 years like clockwork, but if they've already survived 6+ years without any faults, they'll most likely be reliable from then on as well.
Ok, let us say they ll last 4 more years, so 10 years total lifespan.
A PI would last a lot longer.
Why not 50 more years if we're just making up numbers? I still have an IBM thinkpad from 2006 in my possession with everything working. I also see people with Macbooks from the era with the light up apple logo in the wild and at DJs.
>A PI would last a lot longer.
Because you say so? OK, sure.
>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..
I understand what you're saying but saying it isn't enough. There's nothing to support your claim.
One might get lucky with such a laptop, but I won't count on it.
Regarding higher quality components, I think the for the usecase (I mean the kinds of thing it is supposed to be used for) of Raspberry PI, reliability is more important.
This also matches with my experience.
3-5 years of office use for a Pi. [1]
Sure, there's other numbers to find as well, but I'd suggest that they're pretty comparable in the way they handle environments. If one would fail, so would the other.
[0] https://pcpatching.com/2025/11/extend-your-pcs-life-how-long...
[1] https://raspberrypicase.com/how-long-does-a-raspberry-pi-las...
- 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
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.
> [...] 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
I guess. I don't care about the AI hat at all.
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.
Awful how? A SBC can take advantage of many software written from the dawn of x86.
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.
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.
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.
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.
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.
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.
Not true, you're thinking about earlier models.
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.
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.
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.
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.
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].
8GB RAM for AI on a Pi sounds underwhelming even from the headline
Hitching their wagon to the AI train comes with different expectations, leading to a mixed bag of reviews like this.
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).
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?
I daresay they could charge more than a comparably specced computer (if they don't already) and they would still be a viable purchase.
Unless i'm missing something - which is where i'm like why not just buy a NUC with similiar RAM for far less.
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?
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.)
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.
My impression so far was that the resulting models are unusably stupid, but maybe there are some specific tasks where they still perform acceptably?
YOLO for example.
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.
Yes, but that is normal I guess:
Dont need more than 8gb. It'll be enough power. IT can do audio to audio.
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.
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.
TinyML is a book that goes through the process of building a wake word model for such constrained environments.
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.
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.
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.
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.
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
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?
... 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.
