AI HAT vs AI Camera vs AI Kit: Which One Should You Buy?
I’ve been quite interested in Raspberry Pi’s new AI accessories over the past few months, trying to understand what each one does and what makes them different. But between the AI Camera, AI HAT+ and AI Kit, it’s not always obvious which one you actually need, or whether you need one at all.
To be clear, most Raspberry Pi projects don’t need an AI accessory. A Raspberry Pi 5 with 16GB of RAM can perform most basic AI tasks on its own. The AI Camera and AI HAT+ are built for specific projects when faster AI processing is required.
In this guide, I’ll explain what each accessory actually does, where it makes sense, and help you decide whether you should buy one at all.
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Raspberry Pi AI Camera
The Raspberry Pi AI Camera was first released in 2024. It’s basically a camera that connects to your Raspberry PI through the familiar camera serial interface (CSI). In a nutshell, it’s like the official Raspberry Pi Camera Module but with additional AI processing capabilities.
The AI Camera is primarily targeted at computer vision tasks such as image and pose detection. But a Raspberry Pi can perform these functions with any other camera. Then what’s so special about the AI Camera?
How Does the AI Camera Work?
Unlike a normal Raspberry Pi Camera, the AI Camera has an Image Signal Processor (ISP) and an AI Accelerator built into the camera module itself.
This effectively means that, unlike my normal Raspberry Pi camera, which only outputs image data, the AI camera outputs not only image data but also the AI image-processing output (the output tensor).
This relieves the Raspberry Pi of AI processing, because the camera handles the AI model itself using its built-in Neural Processing Unit (NPU). The Raspberry Pi only needs to receive the results and perform any post-processing, such as displaying them on a screen or triggering a home automation task.
Think of it as a smart sensor that not only forwards image data to the Raspberry Pi but also tells it what’s in the image.
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But How Good is the NPU on the AI Camera?
On the surface, the NPU itself (Sony IMX500) doesn’t seem particularly powerful when compared to the Raspberry Pi 5’s onboard CPU, which has 16 GB of RAM.
At first, I expected a standard Raspberry Pi Camera Module paired with the Raspberry Pi 5’s CPU to outperform the AI Camera in AI workloads. After testing both, that wasn’t the case.
The AI Camera significantly outperforms the regular Camera Module + Raspberry Pi 5 in image recognition tasks, achieving up to a 10x improvement in performance (2-5 FPS vs 30 FPS).
From what I understand, this improvement is due to the NPU in the AI camera being optimized for image processing tasks. Unlike the Raspberry Pi processor, which has to perform a bunch of other general tasks, such as loading your OS and managing processes, the NPU is solely focused on executing the AI Model.
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What Models Can Be Used?
AI Models define exactly what your AI Camera does. For example, do you want it to identify objects in the pictures it captures, or do you need it to estimate the person’s emotion or pose? You can find a bunch of models for each task, or you can design and train your own AI models as well.
However, one of the major limitations of the AI Camera, compared to other AI solutions, is its limited support for AI models. When choosing which AI model to run on your AI camera, you have to keep the camera’s resource constraints in mind.
These limitations are because the AI model’s processing is performed entirely in the NPU (Neural Processing Unit) of the AI Camera, and therefore only models that fit within the NPU’s resources are supported.
Luckily, the imx500-models package includes several pre-packaged AI models supported by the AI Camera for tasks such as classification, object detection, semantic segmentation, and pose estimation.
If you have another model or a self-generated one, you can use it with AI Camera as well. However, the model must conform to the AI Camera’s resource limitations.
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Is an AI Camera Worth It?
In my experience, the Raspberry Pi AI Camera is an excellent tool, albeit for a very specific use case: camera- and image-based AI models.
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Check the book hereIn my opinion, for most image detection and classification tasks, it seems like overkill. 2-3 FPS is usually good enough for most object detection tasks, and you only need a 30 FPS feed for advanced workloads where you are sure you need near-real-time processing.
The true strength of an AI camera lies in its compartmentalization. The AI camera handles the entire processing workload, so the Raspberry Pi itself only needs to display the information.
This effectively means you can use the AI camera with any version of Raspberry Pi (e.g., Raspberry Pi Zero) and get much better performance than with Raspberry Pi 5 and a regular camera.
| Raspberry Pi 5 + Pi Camera | Raspberry Pi Zero + AI Camera | |
| Raspberry Pi Price | 300-400$ Amazon Link | 10-30$ Amazon Link |
| Camera Module Price | 20-40$ Amazon Link | 90-100$ Amazon Link |
| Total Price | 320-440$ | 100-130$ |
This flexibility means you can get significantly faster processing at two to three times lower overall price for the project. In my opinion, this makes the AI camera absolutely worth the price.
AI Camera Project Ideas
Here are a few project ideas that I think will be good if you have an AI camera with you.
Smart Home Camera: You can use the AI Camera as an input sensor for home automation functions. For example, you can use an object detection model to check whether any humans are in the room and, based on that, perform actions such as turning on the lights. While this project can be done with a Raspberry Pi 5 and a regular camera, the AI camera will deliver much more stable, reliable performance and make the project much more economical & miniaturized when combined with a cheaper Raspberry Pi Zero.
Wildlife Survey: If you get frequent wildlife visits in your backyard, you can use the AI Camera coupled with a Raspberry Pi to detect which wildlife frequents your backyard and record video only when wildlife is detected, optimizing power and storage space.
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Smart Exercise Assistant: The key advantage of using the AI Camera is the 30 FPS of AI processing that we get. We can use this near-real-time processing, combined with pose estimation, to create a system that tracks our exercise, corrects our pose, and counts our repetitions.
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Raspberry Pi AI HAT+
The Raspberry Pi AI HAT+ is yet another official Pi accessory. Unlike the AI Camera, the AI HAT+ is not limited to image-based projects; it is more of an all-purpose module.
The AI HAT+ can be added to a Raspberry Pi 5 to provide additional computing power specialized for all types of AI-related workloads.
The AI HAT+ gets power from the GPIO header and communicates with the Raspberry Pi via the PCIe Gen 3 interface on the Raspberry Pi 5. Therefore, this HAT can only be used with Raspberry Pi 5 and later versions.
How Does the AI HAT+ Work?
There are three variants of the AI HAT: two original AI HAT+ and one newer AI HAT+ 2. These variants have increasing amounts of compute power, measured in TOPS (Tera Operations Per Second).
A detailed comparison of these variants is as follows:
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| AI HAT+ (13 TOPS) | AI HAT+ (26 TOPS) | AI HAT+ 2 (40 TOPS) | |
| Accelerator chip (Hailo NPU) | Hailo-8L (13 TOPS, INT8) | Hailo-8 (26 TOPS, INT8) | Hailo-10H (40 TOPS, INT4) |
| Memory (RAM) | Uses the memory on a Raspberry Pi 5 | Uses the memory on a Raspberry Pi 5 | Has its own 8 GB onboard memory |
| Use cases | Object detection, camera post-processing, robotics, moderate neural workloads | Object detection, camera post-processing, robotics, moderate neural workloads | Everything available on AI HAT+ plus generative AI workloads, including local LLMs and VLMs |
| MSRP | $70 (check) | $110 (check) | $200 (check) |
Based on this comparison, you can see that these HATs are AI-specific compute modules that add additional computational power to your Raspberry Pi.
Unlike the AI Camera, where the AI workload was completely compartmentalized within the AI Camera module, the AI HAT+ takes a much more generic approach: it adds computational power to the Raspberry Pi while keeping the workload still on the Pi’s processor and resources.
Can it Run LLMs?
Based on this understanding of the AI Camera and the AI HAT+, my first instinct was that while the AI Camera is geared more towards specialized image-processing models, the AI HAT+ is targeted towards generic AI workloads such as generative models and LLMs.
However, this is not the case. Both variants of the AI HAT+ lack onboard memory (DRAM) to run any LLM. In fact, the Hailo-8L and Hailo-8 are specialized for computer vision-related AI processing, not for LLMs.
In fact, if you try to run LLMs with AI HAT+ installed, it might even slow down processing, as the PCIe communication link will bottleneck both processors.
The AI HAT+ 2 solves this problem by introducing 8 GB of DDR4X memory onboard. It is also generally more tuned for LLM-related workloads.
However, during testing, most independent reviewers have found that 8 GB of DDR4x is not enough, and the Raspberry Pi 5 with 16 GB of DDR4x also outperforms the AI HAT+ 2 for running a local LLM.
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Jeff Geerling has written a wonderful review of this topic, and I agree with his conclusion that it’s very difficult to recommend the AI HAT+ 2 for LLM workloads.
How Does it Compare to the AI Camera?
Since both the AI Camera and AI HAT+ are targeted at computer vision tasks, the next question becomes how they compare head-to-head.
The Hailo series of NPUs in the AI HAT+ is significantly more powerful; it can therefore run much more complex AI Models efficiently compared to the AI Camera’s Sony IMX500.
However, what really holds it back is the fact that the AI HAT+ can only be used with Raspberry Pi 5 and later versions. Therefore, this additional processing power comes with quite a hefty price tag.
| Raspberry Pi 5 + AI HAT+ | Raspberry Pi Zero + AI Camera | |
| Raspberry Pi Price | 300-400$ Amazon Link | 10-30$ Amazon Link |
| Module Price | AI HAT+ 70-150$ Amazon Link AI HAT+ 2 200-250$ Adafruit Link | 90-100$ Amazon Link |
| Total Price | 370-650$ | 100-130$ |
On the flip side, in addition to being significantly more powerful than the AI Camera, the AI HAT+ has the added advantage of not being limited to a single sensor. Instead, multiple different sensors can be used with the AI HAT+.
Therefore, in my opinion, the AI HAT+ is capable of much more complex AI Tasks. However, the price difference of the overall project is not justified.
Bonus tip: When I started, the hardest part wasn’t the setup, it was figuring out what to build next. I ended up creating a list of 75+ project ideas with links and difficulty, so it’s easier to just pick something and try it. Grab the list here.
TechWithDavid has done a wonderful comparison with a demo to show how the two options compare and how they compare to a simple Raspberry Pi 5 + camera combination.
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Is The AI HAT+ Worth It?
As I mentioned earlier when discussing the AI camera, for simple object detection or image recognition, we don’t normally need near-real-time processing. In my opinion, the AI HAT+ is overkill for basic computer vision tasks and provides little to no advantage when running generative models and LLMs.
The AI HAT+ is currently limited to the Raspberry Pi 5. These Raspberry Pi models usually have enough computing power to run small-scale AI workloads on their own, and the performance boost from the AI HAT+ doesn’t seem justified unless you have a very specific use case.
The only niche where I see AI HAT+ being useful is when you need to run a computationally intensive image detection, object recognition, or pose estimation task (or a combination of these) that cannot fit within the AI Camera’s available memory limitations.
Another niche where AI HAT+ beats the AI Camera is a workload in which the model takes input from stored images or from multiple or a specific camera sensor, e.g., an IR camera or multiple IP cameras.
AI HAT+ Project Ideas
Here are a few project ideas that an AI HAT+ or an AI HAT+ 2 will actually be good at.
Multi-Camera Security Analytics: The AI HAT+ can also be used with multiple cameras. Therefore, it can serve as the central brain of your smart home security system, making decisions based on input from multiple cameras, such as IP cameras, to detect intrusion.
Autonomous Mobile Robot: The AI HAT+ can be used in an autonomous robot to run a multimodal AI as the robot’s brain, taking input from the camera and other sensors to make movement decisions.
Thermal Camera AI Monitor: A thermal camera can detect people or pets at home or outdoors during the dark hours. This can be useful in a smart home system that needs to detect whether a person has entered a room when it is dark and switch on the lights accordingly.
Raspberry Pi AI Kit
The Raspberry Pi AI Kit is the older, now-discontinued version of the AI HAT+. It’s effectively the same thing as the lowest variant of the AI HAT+, just in a different form factor.
The AI Kit consists of two distinct components: a Hailo-8L NPU (13 TOPS) module in an M.2 form factor and an M.2 HAT as an adapter.
The only slight advantage I can see in the AI Kit is its flexibility. The M.2 HAT can be used for the NPU as well as for an M.2 SSD for a separate project. If you want to learn more about the AI Kit, you can read this detailed article on what the AI Kit is and another article on what projects you can do with an AI Kit.
The Raspberry Pi AI Kit has been discontinued. Overall, if you already have it, I would treat it the same as the AI HAT+ for this article; if you don’t have one yet, I would recommend going with the AI HAT+ instead.
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Final Verdict: Which One Should You Buy?
For most users, I don’t recommend any of these AI Accessories; a Raspberry Pi 5 with 16GB of RAM can perform most basic AI tasks on its own and doesn’t really need an AI accelerator.
However, the exact answer to this question depends largely on your use case. Each of the AI accessories has its own strong suits, which they are actually really good at.
For example, if you don’t have a Raspberry Pi 5 with 16GB of RAM, then the Raspberry Pi AI Camera becomes a very good purchase. The AI Camera + Raspberry Pi Zero is an extremely economical combination that makes the AI Camera worth the price.
I don’t recommend AI HAT+ for most readers. For most use cases, such as computer vision tasks that use a single sensor, it is overkill. And for other tasks such as running local LLMs, the Raspberry Pi 5 16GB outperforms it.
However, the only niche where I see AI HAT+ being a reasonable buy is for enthusiasts that already have a Raspberry Pi 5 and want to try out an AI Accessory; then the basic version of AI HAT+ is slightly cheaper than the AI Camera.
The AI-specific hardware market is rapidly changing, and what might seem like a bad purchase right now might improve significantly in future iterations.
While I don’t really recommend any of the AI accessories for most users. However, there are specific use cases where each accessory still shines. Hopefully this guide has made it clearer what the use case is for each.
Whenever you’re ready, here are other ways I can help you:
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Master your Raspberry Pi in 30 days: If you are looking for the best tips to become an expert on Raspberry Pi, this book is for you. Learn useful Linux skills and practice multiple projects with step-by-step guides.
Master Python on Raspberry Pi: Create, understand, and improve any Python script for your Raspberry Pi. Learn the essentials step-by-step without losing time understanding useless concepts.
Master Linux Commands: Overwhelmed with Linux commands? This book is your essential guide to mastering the terminal. It includes practical tips, real-world examples, and a bonus cheat sheet to keep by your side.
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