The top 5 Axelera AI alternatives for edge computing in 2025

It feels like AI is popping up everywhere, and not just in massive data centers anymore. We’re talking about "edge AI," the brains running right inside our devices. Think smart cameras, factory robots, you name it. Companies like Axelera AI are building the special chips that make this all possible, but they’re definitely not the only game in town.

If you’re in the middle of building an AI-powered product, picking the right hardware is a huge decision. This post breaks down the top five Axelera AI alternatives I’ve found. We’ll look at how they perform, what they’re good at, and what makes them tick, so you can make a choice that actually fits what you’re trying to build. We’ll also ask a bigger question: is custom hardware always the answer, or could a software-first approach get you where you need to go faster?

What is an AI accelerator? The tech behind Axelera AI alternatives

Alright, before we jump into the list, what exactly is an "AI accelerator"? Let’s clear that up.

Think of your computer’s main brain, the CPU, as a jack-of-all-trades. It’s good at juggling a bunch of different tasks. Your graphics card (GPU) is more of a specialist, originally designed for gaming but, as it turns out, pretty great at the heavy math needed to train AI models.

An AI accelerator, also known as an AIPU or NPU, is the ultimate specialist. It’s built for one thing and one thing only: inference. That’s the technical term for using an already-trained AI model to make a decision in the real world, like identifying a person in a video feed.

Because these chips are so focused, they can perform trillions of operations per second (TOPS) using way less power than a GPU. This makes them perfect for devices that run on a battery or can’t be tethered to a server rack, like drones, security cameras, or checkout systems.

How we picked the top Axelera AI alternatives

To create a useful comparison, we looked at a few key things that really matter when you’re trying to build an edge AI product. We wanted to get past the marketing hype and see what each of these platforms could actually do.

Here’s what we focused on:

• Raw Power: This is all about performance, measured in TOPS. It’s the standard industry number for how fast these chips can "think."

• Power Efficiency: Blazing speed doesn’t mean much if it kills your battery in five minutes. We looked at the performance-per-watt to see how much work you get for the energy you put in.

• Ease of Integration: How hard is it to actually get this thing into your product? We looked for standard formats like M.2 and PCIe cards that engineers are already familiar with.

• Developer Friendliness: A powerful chip is just a fancy paperweight without good software. We checked out their software development kits (SDKs), support for common AI models, and the quality of their documentation.

• Price and Availability: Can you actually buy one? And do they tell you the price? A lot of these companies hide their pricing behind a sales call, which can be a real hurdle for small teams just trying to get a project off the ground.

A quick comparison of the top Axelera AI alternatives

Specs don’t tell the whole story, but this table gives you a quick look at how our top five picks measure up against each other.

Competitor	Key Product	Performance (TOPS)	Power Consumption	Form Factor	Ideal Use Case
Hailo	Hailo-8 / Hailo-150	26 --- 150 TOPS	2.5W --- 5W	M.2, PCIe	Smart cameras, retail analytics, industrial automation
d-Matrix	Corsair Platform	Up to 2,000 TOPS (per chiplet)	Data center grade	Custom Chiplet	High-performance generative AI inference in data centers
EnCharge AI	N/A	Varies	Very low	Custom	Power and space-constrained edge devices
SiMa.ai	MLSoC Platform	50 --- 200 TOPS	5W --- 20W	PCIe	Automotive, robotics, drones
Mythic	M1076 AMP	Up to 35 TOPS	~4W	M.2, PCIe	Drones, AR/VR, smart city applications

The 5 best Axelera AI alternatives in 2025

Now for the fun part. Let’s dig into each of the top Axelera AI alternatives and see what makes them stand out.

1. Hailo

You’ve probably run into the name Hailo before. They’ve made a real splash in the edge AI world with their Hailo-8 and the newer Hailo-150 chips. Their main selling point is getting a ton of performance without draining your battery, which is a huge deal for many applications. Plus, their software tools are pretty well-developed, which makes life easier for developers.

• What’s great: Fantastic power efficiency, a solid developer community, and a lot of companies have already integrated their chips.

• What’s not: Their raw performance (TOPS) is lower than some of Axelera AI’s top-tier chips, so it might not be the best fit if you need to run multiple heavy-duty models at once.

• Pricing: Good luck finding a price tag. Like most in this space, Hailo asks you to contact sales for a quote. This can really slow things down if you’re trying to budget a project quickly.

• Best for: Smart retail systems, factory automation, and intelligent security cameras.

2. d-Matrix

d-Matrix is playing a different game. They aren’t focused on small devices but on massive, high-speed inference for generative AI living in data centers. Their Corsair platform is built with a "chiplet" design to handle the intense demands of Large Language Models (LLMs). So, while you wouldn’t put this in a smart camera, it’s a competitor for companies building services that need super-fast, centralized AI.

• What’s great: It’s purpose-built for generative AI, delivering incredible speed for LLM inference.

• What’s not: It’s a data center solution, period. It’s not designed for devices with limited power or space.

• Pricing: This is serious enterprise hardware, so you’ll have to get in touch with their sales team for a quote. Not exactly accessible for a hobbyist or small team.

• Best for: Powering chatbots, content creation tools, and other huge generative AI applications.

3. EnCharge AI

The team at EnCharge AI is attacking the efficiency problem head-on with something called in-memory computing. The goal is to cut down on how much data has to move around inside the chip, which is where a lot of energy gets wasted. Their hardware is aimed at applications where power, energy, and physical size are the absolute biggest concerns.

• What’s great: It has the potential for best-in-class power efficiency, making it perfect for battery-powered gadgets.

• What’s not: They’re a newer player, so their products aren’t as battle-tested, and the software side might not be as mature as the competition.

• Pricing: You guessed it, pricing is customized and you’ll need to go through their contact form. They’re looking for partners and big orders, not selling individual chips off the shelf.

• Best for: Wearables, smart home devices, and anything else where battery life is king.

4. SiMa.ai

SiMa.ai likes to call itself a "software-centric" company. Their big focus is on making it easy for developers to get their AI models up and running. Their MLSoC (Machine Learning System-on-Chip) platform is designed to handle all sorts of computer vision tasks without forcing the user to become a hardware expert.

• What’s great: A big emphasis on being user-friendly with a software-first approach for developers.

• What’s not: You might find better raw performance for your money from competitors who are more focused on pure hardware optimization.

• Pricing: To find out what it costs, you have to ask about their development kit or reach out to their sales department. It’s another gatekeeper that makes it tough to compare costs without getting on the phone.

• Best for: Advanced driver-assistance systems (ADAS) in cars, robotics, and high-end drones.

5. Mythic

Mythic is the wild card of the bunch. They use a unique analog matrix processor (AMP). Instead of using the usual digital 1s and 0s, they perform AI calculations using analog computing inside flash memory. It’s a novel approach that can be incredibly power-efficient, making it a really interesting choice for edge devices that are far from a power outlet.

• What’s great: Their innovative analog tech can lead to extremely low power consumption.

• What’s not: The unique design might mean a steeper learning curve for developers used to traditional digital chips. Also, a bit of a red flag: their website’s contact page was broken when we checked, which isn’t great if you need reliable support.

• Pricing: No public pricing is available. You’ll have to find a way to get in touch with them for details, which could be tricky.

• Best for: Drones, augmented/virtual reality headsets, and video surveillance systems.

This video explores some of the top AI accelerators available in 2025, including several of the Axelera AI alternatives discussed.

Beyond hardware: Do you need custom hardware?

Okay, all this talk of custom chips and TOPS is pretty cool for the hardware nerds among us (no judgment!). If you’re building a fleet of advanced drones from the ground up, one of these accelerators is probably exactly what you need.

But let’s pause for a second. Is that really your goal?

Or are you trying to solve a business problem, like cutting down on repetitive customer support questions? Or giving your team a way to find company info without bugging someone on Slack? For these kinds of goals, the real bottleneck isn’t processing power on a tiny device; it’s the headache of plugging AI into your help desk, chat tools, and all the other software your business runs on.

For a lot of companies, starting a months-long hardware project is a huge detour from what they’re actually trying to accomplish. A software-first approach gets you to the finish line much faster, letting you use AI’s power without having to become a hardware company yourself.

eesel AI: A faster path than custom hardware

This is where switching your mindset from hardware to software can save you a ton of time and money. A platform like eesel AI is built to solve those business problems directly, without you ever having to think about a circuit board.

This workflow illustrates how a software-first solution like eesel AI automates customer support without the need for custom hardware, offering a faster alternative to hardware-based Axelera AI alternatives.

This approach gives you a few major benefits that a hardware project just can’t offer:

• Get started in minutes, not months: You can forget about long waits for hardware and complicated development cycles. With eesel AI, you connect your company’s knowledge sources and launch a working AI agent in minutes. Our one-click setup for tools like Zendesk, Confluence, and Slack means you can start helping customers and employees almost instantly.

• Use the knowledge you already have: There’s no need to build AI models from the ground up. eesel AI learns from your existing help articles, past support tickets, Google Docs, and more. It picks up on your company’s context and tone from day one, so it gives answers that are actually accurate and helpful, no data science team required.

• No hardware headaches: This might be the best part. You get powerful AI automation for your customer service and internal teams without buying, installing, or managing any physical hardware. You can stay focused on making your customers happy, not on managing infrastructure.

Choosing the right AI solution

Choosing the right AI solution starts with being honest about your main goal. If you’re engineering a custom device and need the best possible performance-per-watt for something like computer vision, then digging into the Axelera AI alternatives we’ve discussed, like Hailo and SiMa.ai, is the right move.

However, if your objective is to quickly use AI to solve common business problems, like automating support or making internal knowledge accessible, a hardware project is probably overkill. For a faster, simpler, and more direct path to seeing a return, a software platform like eesel AI lets you bring powerful AI into your existing tools in minutes, not months.

Ready to see how fast you can automate your support?

Start your free eesel AI trial today and deploy your first AI agent in minutes.