Hailo
Edge AI processors for low-power GenAI, vision, and robotics inference.
Hailo is a solid pick for edge teams that need low-power, high-efficiency AI inference without breaking cost targets. The Raspberry Pi HAT+ 2 support is a real differentiator, but the smaller ecosystem means you'll lean on their docs and community more than you would with NVIDIA.
Verified 11d ago · liveness 65/100 · cite: rightaichoice.com/tools/hailo
- Edge AI developers building vision-based security, detection, or OCR systems
- Robotics and drone manufacturers needing on-device inference under 5W
- Automotive ADAS/AD systems requiring real-time, low-latency AI processing
- Smart retail and point-of-sale analytics on the edge
- Cloud-only inference workloads with no edge requirement
- On-chip training—inference-focused only
- High-volume general-purpose computing without AI acceleration
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Skip Hailo if you need a large, mature developer community and extensive third-party hardware ecosystem, or if you must have transparent public pricing before committing to a hardware purchase.
No public pricing—you must contact sales, so expect a slower procurement cycle and potential volume minimums for smaller orders.
Hailo's contact-sales pricing fits volume edge deployments where power and BOM savings offset procurement friction. Compared to NVIDIA Jetson, Hailo often undercuts on cost-per-inference and power draw, but the lack of public tiers means you'll negotiate per unit. For a Raspberry Pi HAT+ 2, the price is accessible to hobbyists, but for professional quantities, budgeting is harder without a quote.
In short
Hailo — Edge AI processors for low-power GenAI, vision, and robotics inference. Best for Edge AI developers building vision-based security, detection, or OCR systems, Robotics and drone manufacturers needing on-device inference under 5W, Automotive ADAS/AD systems requiring real-time, low-latency AI processing. Contact Sales pricing.
Viability Score
How well maintained and how widely used is Hailo? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- DRAM-free AI accelerators for low power edge inference
- Hailo-8L entry-level AI accelerator
- Hailo-8 AI accelerator
- Hailo-8 Century PCIe card for high performance
- Hailo-8R mPCIe module for compact systems
- Hailo-10H AI accelerator for on-device GenAI
- Hailo-15L/H vision processors with integrated ISP
- Generative AI on edge: LLMs and vision transformers
- Hailo Dataflow Compiler for model optimization
- HailoRT runtime for deployment
- Model Zoo with pre-trained vision and GenAI models
- Vision Model Explorer for model selection
- GenAI Example Applications for Raspberry Pi and ASUS
- Hailo OS for vision processor systems
- Hailo Media Library for video processing
About Hailo
Hailo designs edge AI processors and vision SoCs that run deep learning and generative AI on devices where power and cost are tight. The portfolio spans DRAM-free AI accelerators—the Hailo-8L, Hailo-8, Hailo-8R, Hailo-8 Century, and Hailo-10H—and the Hailo-15L and Hailo-15H vision processors with integrated ISPs for camera-based analytics. These chips target applications from security and retail to robotics, ADAS, and smart cockpits, often drawing under 5 watts. The Hailo-10H notably powers the Raspberry Pi AI HAT+ 2 and the ASUS UGen300 USB accelerator, extending on-device GenAI to a wide range of hosts. The Hailo AI Software Suite is central to development. It includes the Dataflow Compiler for model optimization, HailoRT runtime for deployment, and the Model Zoo with pre-trained vision and GenAI models. The Vision Model Explorer helps pick the right model, and GenAI Example Applications offer templates for on-device LLMs and vision transformers. Recent releases—Version 2026-04 for Hailo-10H and Version 2026-01 for Hailo-10H/Hailo-15—show an active software roadmap. Hailo positions itself against the NVIDIA Jetson line, betting on power efficiency and cost. Its DRAM-free accelerators reduce BOM and power compared to traditional solutions, and the company emphasizes physical AI—putting intelligence at the edge rather than in the cloud. Buyers should weigh the smaller developer community against the hardware advantages. If power and cost matter more than ecosystem maturity, Hailo is a strong candidate.
Behind the Verdict
Hailo's core strength is its DRAM-free architecture, which delivers high performance-per-watt for edge inference—a genuine differentiator against NVIDIA Jetson in power-constrained deployments. The Hailo-10H powering the Raspberry Pi AI HAT+ 2 and ASUS UGen300 makes on-device GenAI accessible to hobbyists and industrial developers alike. The software suite (Dataflow Compiler, HailoRT, Model Zoo, Vision Model Explorer) provides a coherent path from model selection to deployment, and the 2026 releases indicate active maintenance. Weaknesses: the developer community is smaller than NVIDIA's, and public pricing is absent—you must contact sales, which slows procurement. The ecosystem of third-party carrier boards and accessories is less extensive. Some advanced model support may require direct vendor engagement. Where it fits: security, retail analytics, robotics, drones, automotive ADAS, and smart cockpits—applications where sub-5W power and low latency matter more than ecosystem breadth. Where it doesn't: cloud-only workloads, on-chip training, or teams needing a large pre-built model hub out of the box. If you're a maker or small team on Raspberry Pi, the HAT+ 2 is a compelling entry point.
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Real-world workflow fit
Concrete scenarios for the personas Hailo actually fits — and what changes day-one when you adopt it.
You need to deploy a YOLO-based object detector on a sub-5W device for local analytics.
Outcome: Using Hailo-8L with the Dataflow Compiler, you compile the model in under an hour, run it with HailoRT, and deploy to production with under 3W power draw—meeting your battery and cost constraints.
You want to run a vision transformer or small LLM on a Raspberry Pi 5 for a robot project.
Outcome: You attach the Hailo-10H via the AI HAT+ 2, follow the GenAI Example Applications, and get on-device inference in a weekend, avoiding cloud latency for your robot's decision-making.
You're evaluating a low-latency, low-power processor for a smart cockpit GenAI assistant.
Outcome: You prototype with the Hailo-8 Century PCIe card, use the Vision Model Explorer to pick a suitable model, and demonstrate real-time LLM inference at under 5W, fitting your thermal budget.
Use Cases
- AI-driven HVAC building management (e.g., Automata Nexus, Apr 2026)
- Real-time object detection for drones
- Smart retail point-of-sale analytics (e.g., Elo POS, Mar 2026)
- Automatic optical inspection in manufacturing
- Vehicle access control with license plate recognition
- Generative AI smart cockpit for automotive
- On-device GenAI via Raspberry Pi HAT+ 2 or ASUS UGen300
Models Under the Hood
as of 2026-08-30
Limitations
- Pricing is not publicly disclosed; you must contact sales for quotes, which may delay procurement for smaller teams.
- The ecosystem of third-party hardware modules is less extensive than NVIDIA Jetson.
- Software maturity is evolving, and some advanced features (e.g., specific model support) may require direct vendor engagement.
as of 2026-08-28
Verification history
We have re-verified Hailo 19 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 19 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Hailo's pricing actually pencils out — and where peers do it cheaper.
Hailo's contact-sales pricing fits volume edge deployments where power and BOM savings offset procurement friction. Compared to NVIDIA Jetson, Hailo often undercuts on cost-per-inference and power draw, but the lack of public tiers means you'll negotiate per unit. For a Raspberry Pi HAT+ 2, the price is accessible to hobbyists, but for professional quantities, budgeting is harder without a quote.
Setup time & first value
How long it actually takes to get something useful out of Hailo — broken out by persona, not the marketing-page minute.
For hardware-savvy developers: from unboxing a Raspberry Pi HAT+ 2 to running a demo takes about 1-2 hours. For a custom board with Hailo-8L, allow a few days to set up the SDK, compile a model, and validate. Teams new to edge AI may spend a week learning the Dataflow Compiler and HailoRT workflow.
Switching to or from Hailo
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Raspberry Pi CPU-only: attach the Hailo AI HAT+ 2 and use GenAI Example Applications to offload inference from the CPU, gaining significant speedup without rewriting your Python code.
- ↗To NVIDIA Jetson: export your Hailo-compiled model, then retrain or recompile with TensorRT; the Dataflow Compiler's ONNX support eases the initial conversion.
Resources & Guides
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Hailo AI Blog: Leading Insights on AI and Edge Computing Page 2
Gain valuable insights into AI technology and industry trends with Hailo's blog page 2, for tech enthusiasts and professionals alike.
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Tutorials & Learning
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