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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsChoose the Raspberry Pi AI Camera when your project is camera-first and you want inference integrated into the Sony IMX500 sensor. Choose AI HAT+ for a Raspberry Pi 5 project that needs a separate vision accelerator, selecting the 13 TOPS or 26 TOPS version according to the model workload. The original AI Kit is discontinued, so it is a legacy or used-market option rather than a sensible new purchase. If you specifically need to run local large language or vision-language models, consider AI HAT+ 2, whose 8 GB of onboard RAM and 40 TOPS INT4 specification target that different workload.
AI HAT vs AI Camera vs AI Kit: the short version
These products solve related but different problems. The AI Camera is a camera module with its own inference processor. AI HAT+ is an accelerator board for Raspberry Pi 5, and you normally pair it with a separate camera when building a vision system. The AI Kit combined an M.2 HAT+ with a Hailo-8L module, but Raspberry Pi no longer produces it. AI HAT+ 2 is a newer, higher-priced board aimed at generative AI as well as vision.
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| Product | Best fit | Inference hardware | Host compatibility | Published price/specification | Current status |
|---|---|---|---|---|---|
| Raspberry Pi AI Camera | Camera-centred projects using supported on-sensor models | Sony IMX500 sensor with integrated AI processor | Raspberry Pi computers with a compatible camera connector; official setup covers Pi 4 and Pi 5, with minor changes for other listed models | $70 US; 12.3 MP sensor; 1080p30 video mode | Production stated through at least January 2028 |
| Raspberry Pi AI HAT+ 13 TOPS | Pi 5 vision projects needing a separate accelerator | Hailo-8L NPU, 13 TOPS | Raspberry Pi 5 | From $70 | Production stated through at least January 2030 |
| Raspberry Pi AI HAT+ 26 TOPS | Pi 5 projects needing the higher listed AI HAT+ tier or more room for concurrent vision models | Hailo-8 NPU, 26 TOPS | Raspberry Pi 5 | From $70 product-family starting price; exact variant pricing can differ by seller and region | Production stated through at least January 2030 |
| Raspberry Pi AI Kit | Existing owners or a carefully checked used purchase | Hailo-8L module, 13 TOPS, supplied with an M.2 HAT+ | Raspberry Pi 5 | No current official price; product discontinued | Raspberry Pi directs new buyers to AI HAT+ |
| Raspberry Pi AI HAT+ 2 | Local LLM and VLM workloads, with vision as an additional use | Hailo-10H, 40 TOPS INT4 and 8 GB onboard RAM | Raspberry Pi 5 | $200 | Production stated through at least January 2036 |
The prices and production dates above are manufacturer-published figures. They are not guarantees of local stock, reseller pricing or a particular region’s tax-inclusive cost.
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How the inference hardware is placed
AI Camera: processing is inside the camera sensor
The AI Camera is built around Sony’s IMX500 image sensor, which includes an AI accelerator. Raspberry Pi described it in its 30 September 2024 launch announcement as “a Sony IMX500 image sensor with an integrated AI accelerator.” In operation, the camera sends an input tensor to that accelerator and returns inference outputs to the Raspberry Pi. The Pi still runs your camera application, user interface, networking and any processing that is not handled by the deployed model.
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This arrangement is useful when the camera is the central component. You do not add a separate AI board merely to obtain the supported IMX500 inference path. You do, however, need to install the required camera software, firmware and a model that can be deployed to the IMX500. Model availability is therefore part of the buying decision, not an afterthought.
AI HAT+: a separate NPU for Raspberry Pi 5
AI HAT+ adds a Hailo neural-processing unit (NPU) as a separate board. Raspberry Pi OS camera frameworks can use that NPU for supported vision tasks after the required software and models are installed. Because the accelerator is not a camera, a camera project also needs a compatible camera module and cable connected to the Pi.
There are two published AI HAT+ capability tiers: 13 TOPS with Hailo-8L and 26 TOPS with Hailo-8. The distinction describes the available accelerator specification. It does not, by itself, promise a particular frame rate, latency or number of simultaneous streams.
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AI Kit: the discontinued bundle
The AI Kit paired an M.2 HAT+ with a Hailo-8L module rated at 13 TOPS. Raspberry Pi’s documentation describes its function as equivalent to the 13 TOPS AI HAT+ variant. The practical difference today is availability and support direction: the kit is no longer in production, and Raspberry Pi recommends AI HAT+ for new customers.
A used kit can still make sense if you already own one or find a verified listing at a worthwhile price. Treat it as legacy hardware, confirm that the Hailo module and M.2 board are both included, and avoid paying a premium simply because the kit is difficult to find.
AI HAT+ 2: a different class of workload
AI HAT+ 2 uses a Hailo-10H and adds 8 GB of onboard RAM. Its headline figure is 40 TOPS at INT4 precision. Raspberry Pi positions it for local large language models (LLMs) and vision-language models (VLMs), not just ordinary camera detection.
For computer vision, Raspberry Pi says AI HAT+ 2 has performance comparable to AI HAT+ 26 TOPS. That statement is a manufacturer comparison, not an independently controlled benchmark. The reason to buy AI HAT+ 2 is the generative-AI capability and onboard memory; do not assume that its 40 TOPS number makes it a universally faster AI Camera or a necessary upgrade for a basic object-detection project.
Rank #2
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Which Raspberry Pi works with each product?
| Requirement | AI Camera | AI HAT+ | AI Kit | AI HAT+ 2 |
|---|---|---|---|---|
| Raspberry Pi 5 | Yes, with a compatible camera connector | Required | Required | Required |
| Raspberry Pi 4 | Official getting-started instructions cover it | No; the board is for Pi 5 | No; the kit is for Pi 5 | No; the board is for Pi 5 |
| Separate camera needed for vision | The camera is integrated into the product | Yes | Yes | Yes |
| Model and software preparation | Required for IMX500 firmware and deployable models | Required for the NPU and supported models | Required for the NPU and supported models | Required for its supported LLM, VLM and vision software |
| Cable consideration | Use the cable appropriate to your Pi’s camera connector | Camera cable depends on the separate camera and Pi | Camera cable depends on the separate camera and Pi | Camera cable depends on the separate camera and Pi |
The AI Camera is the only option in this group whose defining accelerator is in the camera module itself. AI HAT+, AI Kit and AI HAT+ 2 all require a Raspberry Pi 5 host, and a vision build using any of them normally adds a separate camera.
Choose by the job you need to do
Choose AI Camera for a self-contained camera project
Buy the AI Camera when the project starts with an image sensor and the supported inference should happen as close to that sensor as possible. Typical examples include a single camera that identifies selected objects, counts items or triggers an event while the Pi handles control logic and communication.
- You want an integrated camera and accelerator rather than a Pi 5 expansion board.
- Your Raspberry Pi is a Pi 4 or another supported computer with a compatible camera connector.
- Your chosen model is supported by the IMX500 deployment path.
- The $70 US product price fits your budget before adding the Pi, power supply, storage, enclosure and cable.
Do not choose it on the assumption that every TensorFlow, PyTorch or other model can be copied directly onto the sensor. The model has to fit the camera’s supported deployment process, and the host still performs application work outside the accelerator.
Choose AI HAT+ 13 TOPS for a moderate Pi 5 vision workload
The 13 TOPS AI HAT+ is the straightforward current replacement for the discontinued AI Kit. It suits a Pi 5 system that needs supported vision acceleration but does not require the higher published Hailo-8 tier. It is also the sensible baseline when you are comparing a new AI HAT+ against a used AI Kit with the same 13 TOPS Hailo-8L specification.
Remember that the board is an accelerator, not a complete camera system. Budget for the camera, cable and the software/model setup in addition to the HAT.
Choose AI HAT+ 26 TOPS when the model workload justifies it
The 26 TOPS Hailo-8 version gives you the higher listed AI HAT+ tier. It is the more appropriate choice when your supported vision workload needs additional accelerator headroom or you plan to run more demanding or concurrent vision models on a Pi 5.
There is no official head-to-head frame-rate result in the available specifications. “26 TOPS” should therefore be read as a capability specification, not as “twice as many frames per second” in every application. Your model architecture, input resolution, precision, camera count and host-side processing all affect the result.
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- Comprehensive Learning Resources and Support: offers detailed online documentation, video tutorials, prompt technical support, and an active forum community, ensuring beginners can easily complete all projects and enjoy a great experience
Choose AI HAT+ 2 for local generative AI
AI HAT+ 2 is the option to investigate when the requirement explicitly includes a local LLM or VLM. Its 8 GB onboard RAM changes the system design: memory for those workloads is provided on the HAT rather than being limited to the Pi’s ordinary host-memory arrangement.
At $200, it costs substantially more than the starting price of AI HAT+. That premium is difficult to justify for a project whose only task is camera object detection. It is justified by the generative-AI requirement, the onboard memory and the longer stated production horizon through at least January 2036.
What 13 TOPS, 26 TOPS and 40 TOPS actually tell you
TOPS means trillion operations per second, but the figures here come from different accelerator products and, in AI HAT+ 2’s case, are explicitly measured at INT4 precision. They are useful for understanding the manufacturer’s product tiers, not for predicting application performance.
| Figure | Product | How to interpret it |
|---|---|---|
| 13 TOPS | AI HAT+ with Hailo-8L; also the AI Kit’s Hailo-8L module | Entry AI HAT+ accelerator tier for supported Pi 5 vision models |
| 26 TOPS | AI HAT+ with Hailo-8 | Higher AI HAT+ tier for supported Pi 5 vision workloads |
| 40 TOPS INT4 | AI HAT+ 2 with Hailo-10H | Generative-AI-oriented specification with 8 GB onboard RAM; not a universal FPS claim |
Do not compare these numbers as though they were a standardized benchmark across identical precision, memory and software conditions. The published material does not provide an independent, controlled AI Camera-versus-AI HAT+ test, matched FPS figures or energy measurements.
Setup checklist before you buy
AI Camera setup path
- Confirm the host and connector. Check that your Raspberry Pi model has the compatible camera connector and obtain the cable specified for that model.
- Mount the camera carefully. Disconnect power, insert the cable in the correct orientation at both ends, and secure the module before powering the Pi.
- Install the required Raspberry Pi camera software and IMX500 firmware. The official getting-started procedure covers Pi 4 and Pi 5 and notes small changes for other supported models.
- Select a deployable model. Verify that the model is supported for IMX500 inference and follow the model-installation process rather than assuming a generic model file will work.
- Run the camera application and inspect outputs. The Pi receives inference results from the sensor accelerator while it handles the rest of your application.
AI HAT+ or AI Kit setup path
- Start with a Raspberry Pi 5. AI HAT+ and AI Kit are not options for Raspberry Pi 4.
- Install the accelerator board or kit according to its hardware documentation. If buying a used AI Kit, verify that the M.2 HAT+ and Hailo-8L module are both present.
- Connect a compatible camera if the project uses vision. The HAT supplies inference hardware; it does not replace the camera module.
- Install the supported Raspberry Pi OS camera framework, NPU software and model packages. The accelerator is useful only after the software stack recognizes it and your model is supported.
- Test one supported model first. Confirm that inference is being assigned to the Hailo NPU before adding multiple streams or other host-side processing.
AI HAT+ 2 setup path
- Use a Raspberry Pi 5 and install the board as specified.
- Set up the software for the intended LLM, VLM or vision model. Generative models have different memory and software requirements from a conventional detector.
- Use the 8 GB onboard RAM as part of the design. Check the particular model’s support and memory needs instead of treating the 40 TOPS figure as the only requirement.
- Add a camera only if your application needs visual input. AI HAT+ 2 is an accelerator board, not an integrated camera.
Costs, availability and expected product life
The AI Camera is listed at $70 US. AI HAT+ starts at $70, with the 13 TOPS and 26 TOPS versions representing different accelerator specifications. AI HAT+ 2 is listed at $200. The AI Kit has no current official price because it is discontinued.
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|---|---|---|
| Is the product still made? | AI Camera, AI HAT+ and AI HAT+ 2 have stated production horizons; AI Kit is discontinued. | Retail stock, regional distribution and shipping time |
| Is the price universal? | The listed prices are manufacturer figures for the stated products and region where specified. | Tax, currency conversion, reseller markup and bundle contents |
| Will every model run? | Each product requires supported software and models; no universal model list is established by the headline specifications. | Your exact model, input size, precision and software version |
| Will a cable be included? | Cable requirements depend on the Raspberry Pi model and camera connector. | Connector type, cable length and whether a cable is included in the listing |
Raspberry Pi states production for the AI Camera through at least January 2028, AI HAT+ through at least January 2030 and AI HAT+ 2 through at least January 2036. Those dates describe the manufacturer’s stated production commitment; they do not guarantee that every retailer will carry a product continuously.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Common buying mistakes and how to avoid them
Buying AI HAT+ for a Pi 4
AI HAT+ is a Raspberry Pi 5 accessory. If your existing computer is a Pi 4, the AI Camera is the relevant product in this comparison, provided the camera connector and model support meet your needs. Moving to AI HAT+ means budgeting for a Pi 5 as well as the HAT.
Rank #4
- AI-Powered Raspberry Pi Smart Car — PiCar-X: PiCar-X brings AI learning to life — powered by Openclaw and multi-LLMs including ChatGPT, Gemini, Grok, DeepSeek, Qwen, Doubao, Ollama (Local LLMs), and compatible with many more AI platforms. Featuring OpenCV, MediaPipe, TTS & STT, PiCar-X enables true AI vision and voice interaction — it can see, listen, talk, drive and think like an intelligent companion. Ideal for students (10+), educators, and engineers, PiCar-X is the perfect gateway to explore AI, robotics, and machine learning on Raspberry Pi 5/4/3B+/3B/Zero 2W (Raspberry Pi not included)
- Engaging Interactions with Multi-LLMs: PiCar-X, powered by Openclaw and multi-LLMs — including ChatGPT, Gemini, Grok, DeepSeek, Qwen, Doubao, and Ollama (Local LLMs) — and compatible with many other AI platforms, supports voice interaction and visual recognition to make the robot smarter and more responsive. Users can enjoy natural AI conversations, solve math problems through the camera, and interpret gestures, unlocking a world of diverse and fun AI-driven interactions
- Feature-rich and Adaptable: PiCar-X offers engaging applications like line following and obstacle avoidance, supports TTS (Text-to-Speech) and STT (Speech-to-Text) for interactive voice control, and includes a camera for video and vision recognition. It also comes with various sensors, while its customizable design enables a wide range of creative AI and robotics projects
- Versatile Programming Options: Catering to users of all skill levels, PiCar-X supports both Python and Scratch programming languages, allowing for flexible learning and skill development
- Simplified Assembly & Support: PiCar-X is perfect for beginners, yet learning with experienced users is recommended for best results. It comes with easy assembly instructions and forum support for smooth project completion
Assuming the AI Camera needs an AI HAT
The AI Camera’s supported inference accelerator is integrated into the IMX500 sensor. An AI HAT is not required to obtain that camera’s on-sensor inference. You may still need host processing, storage or other accessories for the complete application.
Treating TOPS as guaranteed frame rate
A higher TOPS number does not establish a universal FPS advantage. Compare products using the model, precision, resolution, number of streams and software path you actually intend to run.
Choosing AI HAT+ 2 for ordinary detection without checking the price
AI HAT+ 2’s differentiator is local generative AI and 8 GB of onboard RAM. If your project only detects objects from one camera, the $200 board may provide capabilities you do not use. Start with AI Camera or AI HAT+ according to the camera and Pi requirements.
Buying an AI Kit as though it were a current product
Raspberry Pi no longer produces the AI Kit and directs new customers to AI HAT+. A used kit can be acceptable, but check the module, HAT, physical condition, seller return policy and compatibility before paying.
Ignoring model support until after purchase
Neither an integrated accelerator nor a separate NPU makes every model plug-and-play. Confirm the supported deployment route for your exact model before ordering hardware. This is especially important when moving from ordinary vision inference to an LLM or VLM.
A practical decision matrix
| If your priority is… | Start with… | Reason |
|---|---|---|
| An integrated camera and supported inference | AI Camera | The IMX500 contains the accelerator and the product is designed around camera-first use. |
| Vision acceleration on a Pi 5 at the lower listed tier | AI HAT+ 13 TOPS | It is the current 13 TOPS Hailo-8L option and the closest new-product counterpart to the discontinued AI Kit. |
| More AI HAT+ accelerator headroom for supported vision models | AI HAT+ 26 TOPS | It uses the higher listed Hailo-8 tier, without claiming a fixed FPS multiplier. |
| Local LLM or VLM execution | AI HAT+ 2 | It adds 8 GB onboard RAM and is the family member documented for generative-AI workloads. |
| Reusing hardware already on hand | AI Kit, if complete and tested | Its 13 TOPS Hailo-8L function is still documented, but it is discontinued and should not be treated as the default new purchase. |
Bottom line for most buyers
Buy the AI Camera when the camera itself is the product you need and its supported IMX500 models cover your application. Buy AI HAT+ for a Raspberry Pi 5 system that needs a separate vision accelerator, choosing 13 TOPS for a moderate workload and 26 TOPS when the higher listed tier is justified. Skip the discontinued AI Kit unless you are deliberately reusing or carefully sourcing used hardware. Choose AI HAT+ 2 only when local LLM or VLM capability and its 8 GB onboard RAM matter; its 40 TOPS INT4 figure should not be mistaken for a universal camera-performance guarantee.
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