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10 top AI hardware and chip-making companies in 2026
Due to rapid AI hardware advancement, companies release advanced products yearly to keep up with the competition. The new competitive product on the market is the AI chip.
The AI hardware market is evolving rapidly, with companies pushing the boundaries of performance, efficiency and innovation. As the industry grows, these advancements will shape the future of AI applications across various sectors.
The following 10 companies are competing to create the most powerful and efficient AI chip on the market.
10 top companies in the AI hardware market
The following AI hardware and chip-making companies are listed in alphabetical order.
Alphabet
Alphabet, Google's parent company, offers various products for mobile devices, data storage and cloud infrastructure.
Alphabet has focused on producing powerful AI chips to meet the demand for large-scale projects. In December 2024, Alphabet released a new quantum computing chip, Willow. With 105 qubits and the ability to scale up, the Willow chip reduces error in quantum computing faster and more accurately than its predecessors.
Ironwood TPU is the company's newest product, released in November 2025, designed to support the new age of inference. It scales up to 9,216 chips per pod, making it 24 times more powerful than El Capitan, the world's largest supercomputer.
AMD
AMD is expanding its AI hardware portfolio with new processors and GPUs.
AMD released its latest CPU microarchitecture chip design, Zen 5, in January 2025. In January 2026, AMD released its next generation of Ryzen processors, the Ryzen AI Embedded P100 and X100 Series. The P100 Series processors are designed for human-machine interface and industrial automation, featuring four to six CPU cores -- eight to twelve cores planned for later in 2026. The X100 Series scales up to 16 CPU cores for high-performance, compute-intensive tasks, such as advanced autonomous systems and robotics.
AMD's Instinct MI300 Series chip, MI325X, was released in 2024. This upgrade from MI300X has a larger bandwidth of 6 TBps. The MI350 series, including the MI355X chip, was released in June 2025. The MI355X chip is 4 times faster than the MI300X. These AI GPU accelerators are meant to rival Nvidia's Blackwell B100 and B200.
Apple
Apple Neural Engine, specialized cores based on Apple chips, has furthered the company's AI hardware design and performance. Neural Engine led to the M1 chip for MacBooks. Compared to the generation before, MacBooks with an M1 chip are 3.5 times faster in general performance and five times faster in graphics performance.
After the success of the M1 chip, Apple announced further generations. As of 2025, Apple has released the M5 chip. This chip has a 10-core GPU with Neural Accelerators in each core, delivering over 4x the AI performance of the M4 chip.
Apple and Broadcom are developing an AI-specific server chip, Baltra. This chip is expected to be released in 2026, but it will only be used internally by the companies to handle inference tasks.
AWS
AWS is focusing on AI chips for cloud infrastructure. Its Elastic Compute Cloud (EC2) Trn3 instances are purpose-built for running AI training and inference workloads. They use AWS Trainium AI accelerator chips to function.
The Trn3 UltraServer, released in December 2025, has 144 Trainium3 chips and performs over four times better than Trainium2 UltraServers. The Trainium3 is also 40% more energy-efficient than previous generations.
In 2024, AWS released Graviton4, a 96-core ARM-based processor ideal for a range of cloud workloads, such as databases, web servers and high-performance computing. The fourth generation of AWS's Graviton processor, which powers EC2 R8g instances, delivers up to 30% better performance and offers three times the vCPUs and memory of Graviton3.
Cerebras Systems
Cerebras is making a name for itself with the release of its third-generation wafer-scale engine, WSE-3. WSE-3 is deemed the fastest processor on Earth with 900,000 AI cores on one unit. Every core has access to 21 petabytes per second of memory bandwidth.
Compared to Nvidia's H100 chip, WSE-3 has 7,000 times larger bandwidth, 880 times more on-chip memory and 52 times more cores. This WSE-3 chip is also 57 times larger in area, so more space is necessary to house the chip in a server.
IBM
Telum was IBM's first specialized AI chip, and Telum II was released in late 2025. IBM has also set out to design a powerful successor to rival its competitors.
In 2022, IBM created the Artificial Intelligence Unit. The AI chip is purpose-built and runs better than the average general-purpose CPU. Based on a similar architecture, IBM released the Spyre Accelerator in 2025. Spyre has 32 AI accelerator cores and contains 25.6 billion transistors over 14 miles of wire. The Spyre Processor enables on-premises, low-latency inferencing for tasks like real-time fraud detection, intelligent IT assistants, code generation and risk assessments.
IBM is working on the NorthPole AI chip, which does not have a public release date. NorthPole differs from IBM's TrueNorth chip. The NorthPole architecture is structured to improve energy use, decrease the amount of space the chip takes up and provide lower latency. The NorthPole chip is set to mark a new era of energy-efficient chips.
Intel
Intel has made a name for itself in the AI hardware market with its AI processors and GPUs.
Xeon 6 processors launched in 2024 and have been shipped to data centers. These processors offer up to 288 cores per socket, enabling faster processing time and enhancing the ability to perform multiple tasks at once.
Intel has released the Gaudi 3 GPU chip, which competes with Nvidia's H100 GPU chip. The Gaudi 3 chip trains models 1.5 times faster, outputs results 1.5 times faster, and uses less power than Nvidia's H100 chip. The Jaguar Shores GPU chip, the successor to the Gaudi 3 chips, is still set to launch in 2026. This chip will focus on energy efficiency.
In late 2024, Intel released the Core Ultra AI Series 2 processors. The release included multiple processors under the Core Ultra 200 series, including 200H, 200HX, 200S and 200V. Each series focuses on specific features, such as enhanced security, AI capabilities, performance and energy efficiency. The Core Ultra 200 processor series is designed for desktop and mobile platforms, creating AI PCs.
Nvidia
Nvidia became a strong competitor in the AI hardware market when its valuation surpassed $1 trillion in early 2023. The company's current work includes its B300 chip, Blackwell GPU microarchitecture and Vera Rubin. Nvidia also offers AI-powered hardware for the gaming sector.
The Blackwell GPU microarchitecture is replacing the Grace Hopper platform. Blackwell is 2.5 times faster and 25 times more energy-efficient than its predecessors. The Blackwell microarchitecture is designed to increase efficiency with scientific computing, quantum computing, AI and data analytics. The B300 chip series, or Blackwell Ultra, was released in the second half of 2025.
Vera Rubin is Nvidia's next-generation GPU superchip architecture, expected to be released in late 2026. It combines the Vera CPU with the Rubin GPU, the successor to Blackwell.
Qualcomm
Although Qualcomm is relatively new in the AI hardware market compared to its counterparts, its experience in the telecom and mobile sectors makes it a promising competitor.
Qualcomm's Cloud AI 100 chip beat Nvidia H100 in a series of tests. One test was to see the number of data center server queries each chip could carry out per watt. Qualcomm's Cloud AI 100 chip totaled 227 server queries per watt, while Nvidia H100 hit 108. The Cloud AI 100 chip also managed to net 3.8 queries per watt compared to Nvidia H100's 2.4 queries during object detection.
In 2024, Qualcomm released Snapdragon 8s Gen 3, a mobile chip that supports 30 AI models and has generative AI features, like image generation and voice assistants. Later in the year, the company released the newest version, Snapdragon 8 Elite, which improved AI performance by 45%. The Snapdragon 8 Elite Gen 2 was released in late 2025 and offers 30% more CPU power than the first generation.
Tenstorrent
Tenstorrent builds computers for AI and is led by the same man who designed AMD's Zen chip architecture, Jim Keller. Tenstorrent offers multiple hardware products, including its Wormhole processors and Galaxy servers, which together form the Galaxy Wormhole Server.
Tenstorrent released the Blackhole series, an AI accelerator, in April 2025. It has 16 RISC-V cores and 32 GB of GDDR6 memory per chip. The p100a chip has 120 Tensor Cores and 28 GB of GDDR6. The p150a has 140 Tensor Cores and 32 GB of GDDR6. Both chips operate at up to 300 Watts.
Wormhole n150 and n300 are Tenstorrent's scalable GPUs. N300 nearly doubles every spec of n150. These chips are for network AI and are put into Galaxy modules and servers. Each server holds up to 32 Wormhole processors, 2,560 cores and 384 GB of GDDR6 memory.
Kelly Richardson is site editor for Informa TechTarget's SearchDataCenter site.
Devin Partida is editor in chief of ReHack.com and a freelance writer. She has knowledge of niches such as biztech, medtech, fintech, IoT and cybersecurity.
