With popularity and progress surged, AI hardware became a highly competitive market. AI hardware companies need to quickly turn around product advancements to have the latest and most effective products in the market.
These 10 AI hardware companies focus on CPU and data center technology, but their specializations are gradually expanding as the market expands. Today, these companies are competing to create the most powerful and efficient AI chips on the market.
10 top companies in the AI hardware market
The following AI hardware and chip manufacturers are listed alphabetically:
alphabet
Google's parent company, Alphabet offers a wide range of products for mobile devices, data storage and cloud infrastructure.
The TPU V6E is the latest Trillium chip released in October 2024. This chip is similar to the TPU V5E, with a pod size of 256 chips and four ports per chip. However, the TPU V6E chip has 4.7 times higher per chip peak calculation performance than the TPU V5E. The Ironwood TPU V7 has 9,216 chips per pod and is expected to be released at the end of 2025.
Alphabet focuses on creating powerful AI chips to meet the demands of large-scale projects. In December 2024, Alphabet released Willow, a new quantum computing chip. With 105 qubits and scale-up capabilities, WillowTip reduces quantum computing errors faster and more accurately than its predecessors.
AMD
AMD released its latest CPU microarchitecture chip designs, the Zen 5 and the next generation Ryzen 300 and 200 series, in early January 2025.
AMD's MI300 series chip, the MI325X, was released in 2024. The bandwidth for this upgrade from the MI300X is 6 Tbps. The MI350 series, which includes the MI355X chip, was released in June 2025. The MI355X chip is four times faster than the MI300X. These AI GPU accelerators are intended to rival Nvidia's Blackwell B100 and B200.
apple
Apple Neural Engine is a specialized core based on Apple chips, furthering the design and performance of its AI hardware. The neural engine led to the MacBook's M1 chip. Compared to previous generations, MacBooks with the M1 chip are 3.5 times faster than typical performance and 5 times faster graphics performance.
After the success of the M1 chip, Apple announced more generations. As of 2024, Apple released the M4 chip. The M4 chip has a neural engine that is three times faster than the M1 chip and 1.5 times faster than the M2. The M5 chip is scheduled to be released in the fall of 2025.
Apple and Broadcom are developing Baltra, an AI-specific server chip. The chip is scheduled to be released in 2026, but companies will only use it internally.
aws
AWS has switched its focus from cloud infrastructure to chips. Its elastic computation cloud (EC2) TRN1 instances are dedicated for deep learning and large-scale generative models. They use AWS Trainium Ai Acelerator chips to work.
AWS Inference is a machine learning chip that generates high-performance inference predictions at a low cost. Trainium Accelerators train models, and guesswork accelerators deploy models. The TRN1.2XLARGE instance was the first iteration. There was one training accelerator, 32 GB of instance memory, and 12.5 GBPS network bandwidth.
AWS has EC2 TRN2 instances and Ultraserver. The TRN2 instance has 16 Trainium2 chips, 1.5 TB of accelerator memory and 46 TBPS bandwidth. The TRN2 Ultraserver has 64 Trainium2 chips, 6 TB of shared accelerator memory, and 185 TBPS bandwidth on four TRN2 instances. The Trainium3 chip is scheduled to be released in the second half of 2025. Ultracellver with Trainium3 delivers 4x better performance than Trainium2 Ultraservers.
In 2024, AWS released Graviton4, a 96-core arm-based processor that is ideal for a variety of crowd workloads, including databases, web servers, and high-performance computing. The fourth generation of AWS' Graviton processors that drive EC2 R8G instances offer up to 30% better performance and has three times the VCPU and memory that is Graviton3.
Celebrus System
Celebras has given its own name with the release of WSE-3, the third-generation wafer-scale engine. The WSE-3 is considered the fastest processor on the planet with 900,000 AI cores per unit. All cores have access to 21 petabytes of memory bandwidth per second.
Compared to Nvidia's H100 chip, the WSE-3 has 7,000x bandwidth, 880x on-chip memory and 52x cores. This WSE-3 chip requires 57 times larger in area, so it takes up space to accommodate the chips on a server.
IBM
Telum is IBM's first specialized AI chip, and Telum II is expected to be released in late 2025. IBM is also planning to design a strong successor that rivals its competitors.
In 2022, IBM created an AI unit. The AI chip is dedicated and is better than the average general purpose CPU. Based on a similar architecture, IBM will release Spyre Accelerator in 2025. Spyre has 32 AI accelerator cores and includes 25.6 billion transistors over 14 miles of wire.
IBM is working on the Northpole AI chip, which has no release date. Northpole is different from IBM's Truenorth chip. The North Pole architecture is configured to improve energy use, reduce the amount of space the chips will take up, and provide a drop. North pole tips are set to mark a new era of energy-efficient chips.
Intel
Intel has used AI products to name itself in the CPU market.
The Xeon 6 processor was launched in 2024 and shipped to the data center. These processors offer up to 288 cores per socket, reducing processing time and improving the ability to perform multiple tasks at once.
Intel has released a Gaudi 3 GPU chip that competes with Nvidia's H100 GPU chip. The Gaudi 3-chip training model is 1.5 times faster, outputs 1.5 times faster results, and uses less power than Nvidia's H100 chip.
Intel has cancelled the release of its Falcon Shores AI GPU chip. The Jaguar Shores chip, the successor to the Gaudi 3 chip, is still scheduled to be released in 2026. However, the company is focusing on the standalone AI accelerator.
In late 2024, Intel released the Core Ultra AI Series 2 processor. This 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 exceeded $1 trillion in early 2023. The company's current work includes a B200 chip, a Blackwell GPU microarchitecture and Vera Rubin. Nvidia also offers AI-powered hardware for the gaming sector.
The Blackwell GPU microarchitecture will replace the Grace Hopper platform. Blackwell is 2.5 times faster and 25 times more energy efficient than its predecessor. The Blackwell microarchitecture is designed to improve efficiency through scientific computing, quantum computing, AI, and data analysis. The B300 Chip Series, or Blackwell Ultra, is scheduled to be released in the second half of 2025.
Vera Rubin is Nvidia's next-generation GPU SuperChip Architecture, scheduled to be released in the second half of 2026. It combines VeraCPU with the Rubin GPU, the successor to Blackwell.
Qualcomm
Qualcomm is relatively new in the AI hardware market compared to its counterparts, but its experience in the telecom and mobile sector makes it a promising competitor.
Qualcomm's Cloud AI 100 chip defeated the Nvidia H100 in a series of tests. One test was to see how many data center server queries each chip could perform per watt. Qualcomm's Cloud AI 100 chip totaled 227 server queries per watt, and the NVIDIA H100 hit 108. The Cloud AI 100 chip was able to net as many as 3.8 queries per watt, compared to the 2.4 queries on NVIDIA H100 during object detection.
In 2024, Qualcomm released the Snapdragon 8S Gen 3, a mobile chip that supports 30 AI models and has generation AI capabilities such as image generation and voice assistant. Later in the year, the company released its latest version of the Snapdragon 8 Elite, improving AI performance by 45%. The Snapdragon 8 Elite Gen 2 is scheduled to be announced in September 2025.
Tenstorrent
Tenstorrent is led by the same man who built a computer for AI and designed AMD's Zen chip architecture, Jim Keller. Tenstorrent has multiple hardware products that create Galaxy Wormhole servers, such as Wormhole processors and Galaxy servers.
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 a maximum of 300 watts.
The Wormholes N150 and N300 are TenStorrent scalable GPUs. The N300 almost doubles all specifications of the N150. These chips are for network AI and can be placed in Galaxy modules and servers. Each server holds up to 32 wormhole processors, 2,560 cores, and 384 GB of GDDR6 memory.
Editor's Note: This article was updated in July 2025 to reflect the AI chips and processors offered by each company.
Devin Partida is Editor-in-Chief of Rehack.com and freelance writer. She has knowledge of niches such as Biztech, Medtech, Fintech, IoT, and cybersecurity.
Kelly Richardson is the site editor for Informa TechTarget's SearchDatacenter site.
