Analyzing Cerebras Systems (NASDAQ:CBRS) & Ambiq Micro (NYSE:AMBQ)

Cerebras Systems (NASDAQ:CBRS) and Ambiq Micro (NYSE:AMBQ) are both manufacturing companies, but which is the superior business? We will contrast the two businesses based on the strength of their institutional ownership, valuation, dividends, analyst recommendations, earnings, profitability and risk.

Valuation and Earnings

This table compares Cerebras Systems and Ambiq Micro”s revenue, earnings per share (EPS) and valuation.

	Gross Revenue	Price/Sales Ratio	Net Income	Earnings Per Share	Price/Earnings Ratio
Cerebras Systems	$509.99 million	90.66	N/A	N/A	N/A
Ambiq Micro	$72.51 million	24.58	-$36.46 million	($20.69)	-4.03

Cerebras Systems has higher revenue and earnings than Ambiq Micro.

Profitability

This table compares Cerebras Systems and Ambiq Micro’s net margins, return on equity and return on assets.

	Net Margins	Return on Equity	Return on Assets
Cerebras Systems	N/A	N/A	N/A
Ambiq Micro	-46.86%	-45.10%	-16.29%

Analyst Ratings

This is a breakdown of current recommendations for Cerebras Systems and Ambiq Micro, as provided by MarketBeat.

	Sell Ratings	Hold Ratings	Buy Ratings	Strong Buy Ratings	Rating Score
Cerebras Systems	0	0	0	0	0.00
Ambiq Micro	1	3	3	0	2.29

Ambiq Micro has a consensus price target of $52.80, suggesting a potential downside of 36.66%. Given Ambiq Micro’s stronger consensus rating and higher possible upside, analysts plainly believe Ambiq Micro is more favorable than Cerebras Systems.

Summary

Cerebras Systems beats Ambiq Micro on 5 of the 8 factors compared between the two stocks.

About Cerebras Systems

We are building the fastest AI infrastructure in the world. In AI, speed is critical to win. Speed improves user engagement, expands product capabilities, can lower operating costs, and opens new markets. It shortens iteration cycles for engineers, researchers, and professionals across industries, allowing them to be more productive. Speed unlocks new applications and new industries. In technology, “speed unlocking value” is a pattern that has repeated itself over the past 30 years. Faster solutions are used more often and for more demanding tasks. For example, the speed of broadband transformed the internet from static pages into real-time applications, enabling new products and industries. Similarly, in search, Google showed that even short delays in delivering answers significantly reduced usage and engagement. AI repeats this pattern. As AI has moved from novelty to necessity, AI work has grown more demanding, and speed has become a bottleneck. Faster AI does more work in less time, providing better answers sooner. Our solutions are built for speed. Cerebras Inference delivers answers up to 15 times faster than leading GPU-based solutions as benchmarked on leading open-source models. Similarly, many customers have achieved more than 10 times faster training time-to-solution compared to leading GPU systems of the same generation. These performance breakthroughs are the result of our core innovation: the world’s first and only commercialized wafer-scale processor. Called the Wafer-Scale Engine (“WSE”), our processor is 58 times larger than NVIDIA’s B200 chip and has 2,625 times more memory bandwidth than NVIDIA’s B200 package, which contains two individual chips. To build the WSE, we solved the 75-year-old compute industry problem of wafer-scale integration to produce, yield, power, and cool a chip of this size. This size is what enables our incredible AI speeds. By bringing massive compute and memory onto a single piece of silicon and integrating it into a purpose-built system and software stack, we deliver exceptional AI speed for customers on premises and via the cloud. Our strategic partners and customers include hyperscalers, foundation model labs, AI-native and digital-native businesses, enterprises, and Sovereign AI initiatives. OpenAI, the world’s leading foundation model lab, selected us to be its fast inference solution. With Cerebras, OpenAI’s Codex-Spark users turn ideas into working software in seconds. Amazon Web Services (“AWS”), the world’s leading hyperscale cloud, has signed a binding term sheet with us to become the first hyperscaler to deploy Cerebras in its own data centers, providing massive distribution to a broad base of enterprise customers. Our customers use Cerebras solutions to run applications that demand speed, scale, and intelligence. This work includes training and serving large frontier models with near-instant responses, processing massive datasets in real time, and generating full-stack applications in a single step. Once customers adopt fast inference, user expectations for interactivity rise, and engineering teams shift from latency optimizations to other work, making it difficult to return to slower inference. We deliver our solutions to customers in several different ways. Organizations that require full data and infrastructure control can purchase Cerebras AI supercomputers for on-premises deployments. Customers seeking cloud flexibility can access Cerebras compute through consumption-based models on Cerebras Cloud or through partner clouds. For example, our high-speed inference services are available through partners, including AWS Marketplace, Microsoft Marketplace, IBM watsonx Model Gateway, Vercel AI Gateway, OpenRouter, and Hugging Face, enabling seamless adoption within existing workflows. Our ability to deliver differentiated performance has made us a strategic partner to many of our largest customers. Beyond providing compute infrastructure, we provide AI services to our customers to co-develop solutions to address their most complex challenges, from training state-of-the-art models to optimizing deployments for each application’s needs. These partnerships have expanded over time; notably, our top ten customers by year-to-date revenue through December 31, 2025 increased their aggregate spend with us by approximately 80% within 12 months of their initial purchase, often including contracts for co-development. AI is one of the fastest growing technologies in history. We believe that our high-speed AI solutions give us a meaningful competitive advantage in this market. We believe that further adoption of AI, accelerated by increased penetration, more frequent usage, and more complex applications, will continue to rapidly expand the market. According to IDC, investments in AI solutions and services are projected to yield a global cumulative impact of $22.3 trillion by 2030, representing approximately 3.7% of the global gross domestic product (“GDP”). The combined market for AI training infrastructure and our addressable market within AI inference is estimated to be $251 billion in 2025 and is expected to grow to $672 billion by 2029—a 28% CAGR, according to Bloomberg Intelligence. This estimate indicates that AI inference will grow more than twice as fast as AI training infrastructure through 2029. With the fastest inference platform on the market, as benchmarked by Artificial Analysis, and a proven track record in large-scale training, we believe we are well-positioned to capture growth across both parts of the AI infrastructure market. Our growth reflects the broader acceleration of AI adoption. We were incorporated in April 2016 as a Delaware corporation. Our principal executive offices are located in Sunnyvale, California.

About Ambiq Micro

Our mission is to enable intelligence (artificial intelligence (AI) and beyond) everywhere by delivering the lowest power semiconductor solutions. We are a pioneer and leading provider of ultra-low power semiconductor solutions designed to address the significant power consumption challenges of general purpose and AI compute – especially at the edge. Our customers rely on Ambiq to deliver AI compute closer to end users (edge environments) where power consumption challenges are the most severe. Our leading position is built upon our hardware and software innovations that deliver two to five times lower power consumption than traditional semiconductor designs. Our products power over 270 million devices today. We shipped more than 42 million units in 2024, and we estimate that over 40% of them ran AI algorithms. We seek to drive growth in AI adoption at the edge in the personal devices, medical/healthcare, industrial edge, and smart home and building markets and continue to set new standards in edge AI performance and power efficiency. Over time, we expect to integrate our ultra-low power technology into additional chip products that benefit from greater power efficiency, including high-performance compute applications such as AI data centers and automotive. AI is perhaps the most disruptive and revolutionary technology trend of recent history, estimated to represent $23 trillion of global annual spend by 2040, according to McKinsey. AI use cases continue to permeate our lives and improve our daily productivity by enabling us to interact with devices via voice and gestures, unlock our homes with facial recognition, track health accurately and intelligently, and hold clear calls amidst loud background noise. To date, a majority of AI compute has been deployed in data centers due to its large physical scale and the need for wall plug energy, as AI compute requires enormous and steady energy resources. At the edge, however, power limitations have been especially acute due to small device size and limited battery life. We believe this greatly constrains the potential of AI to improve our daily, on-the-go lives. Enabling AI at the edge – where the action takes place – with vastly improved power efficiency will allow faster real-time decision-making due to data proximity, greater data privacy, higher energy efficiency from reduced network usage, and less dependence on constant costly connections to the cloud. We believe new AI use cases will only be possible if edge devices are much more power efficient. Our proprietary Sub-threshold Power Optimized Technology (SPOT) platform is designed to fundamentally and cost-effectively reduce power consumption of battery- and wireline-powered devices alike. Depending on the application, devices incorporating SPOT demonstrate a two to five times reduction in power consumption compared to conventional integrated circuit designs. SPOT is a ground-breaking approach at the chip design level that incorporates sub- and near-threshold hardware without using expensive manufacturing processes. We provide a full-stack solution encompassing tightly integrated hardware and software. Our solutions include a diverse family of systems-on-chip (SoCs) and the software required to enable on-chip AI processing, general compute, sensing, security, storage, wireless connectivity, and advanced graphics. Our SoC solutions deliver compute at a very small fraction of the power consumed by our competitors’ products. Our ultra-low power SoCs serve a wide range of markets requiring on-device and real-time AI, including smartwatches and fitness trackers, augmented and virtual reality (AR/VR) glasses, smart rings, digital health monitors, security systems and access control, livestock tracking, crop monitoring, and factory automation. These devices increasingly offer on-chip AI-powered features such as speech recognition, domain-specific language models, image and video processing, and sensing, further straining power consumption, which our solutions are positioned to address. As global demand for our SoC solutions accelerates, our sales and marketing efforts are increasingly focused on our end customers in target geographies such as the United States, Europe, and Asia (ex-MainlandChina). We were incorporated in Delaware on January 20, 2010 under the name Cubiq Microchip, Inc., and in October 2012, changed our name to Ambiq Micro, Inc. Our principal executive offices are located in Austin, Texas.