If You Invested in Cerebras Systems (CBRS)
Looking for the current price? See the CBRS quote & overviewWhat $1,000 or $10,000 in CBRS Would Be Worth Now
Real historical value by amount invested and how long ago| If you invested | 1 year ago | 5 years ago | 10 years ago | Since May 14, 2026 |
|---|---|---|---|---|
| $1,000 | — | — | — | $535 -46% |
| $10,000 | — | — | — | $5,350 -46% |
Based on real historical closing prices, dividend- and split-adjusted, through the latest market close. Past performance does not guarantee future results.
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Choose your own date and amount for CBRS$1,000 Investment Over Time
CBRS vs S&P 500Year-by-Year Returns
CBRS annual performance| Year | Start Price | End Price | Annual Return | Cumulative |
|---|---|---|---|---|
| 2026 | $311.07 | $166.43 | -46.5% | -46.5% |
About Cerebras Systems
Technology · NASDAQ
Cerebras Systems Inc. Overview
Cerebras Systems Inc. (NASDAQ: CBRS) is an AI infrastructure company based in Sunnyvale, California. The company designs infrastructure for artificial intelligence training and inference, with a focus on high-speed compute systems built around its wafer-scale semiconductor technology. Cerebras describes its platform as the world’s fastest AI infrastructure and says it builds the world’s largest semiconductor, along with the systems needed to power, cool, and supply data to its processors.
The company’s business is centered on making advanced AI workloads run faster. Its infrastructure is used for two core parts of AI computing: training, where models learn from large data sets, and inference, where trained models generate responses or predictions. Cerebras sells and delivers these capabilities through systems that can be used on premises and through cloud access.
Core Technology
Cerebras is known for its Wafer-Scale Engine, a semiconductor design used as the foundation for its AI compute systems. The company pairs its processors with hardware systems that handle power, cooling, and data movement. That full-system approach matters because high-performance AI workloads are limited not only by raw chip speed, but also by how quickly data can reach the processors and how effectively the system can operate under heavy compute demand.
Cerebras also develops software that links its systems together into AI supercomputers. The company states that its software supports familiar machine learning frameworks, including PyTorch, which helps AI teams use Cerebras infrastructure without building around an unfamiliar programming model. This software layer is an important part of the company’s identity because it connects the semiconductor, the system design, and the user workflow.
Training and Inference Workloads
Cerebras infrastructure is designed for both AI model training and AI inference. Training requires large amounts of compute over extended runs, while inference often depends on low latency and high output speed. The company has described its systems as supporting large model training and fast inference, and recent company materials have emphasized inference speed as a key use case.
Customers use Cerebras supercomputers to train AI models, and Cerebras also uses those systems to run inference for customers. The company says its inference performance reaches speeds not available from alternative commercial technologies. Because inference is the point where users interact with AI models, speed can affect the user experience, the economics of serving models, and the kinds of AI applications that can be practical.
Products and Deployment Model
Cerebras builds AI systems around its wafer-scale processors rather than selling only a standalone chip. Its disclosed offering includes processors, AI systems, power and cooling design, data-feeding systems, and software that connects multiple systems into supercomputers. This gives the company a vertically integrated role in AI infrastructure: it designs the semiconductor, builds the system around it, and provides the software needed to operate at larger scale.
The company delivers its AI capabilities in two ways: on-premise deployments and cloud access. On-premise systems place Cerebras hardware at a customer or partner environment. Cloud delivery allows customers to access Cerebras compute without owning the physical system directly. Both models are part of the company’s stated approach to making its AI infrastructure available to users.
Customers and Use Cases
Cerebras says global corporations, research institutes, and governments choose its systems to run AI workloads. Its disclosed customer and partner references include organizations using or integrating Cerebras compute for high-speed inference and large-scale AI work. The company’s role is tied to demand for compute capacity that can support advanced models, production AI applications, and latency-sensitive inference.
Because Cerebras focuses on AI infrastructure rather than consumer software, its news and filings often center on capacity agreements, cloud demand, customer warrants, product systems, and partnerships that help deliver compute. Investors researching CBRS stock should understand that the company’s operating story is linked to the buildout of AI compute capacity and the adoption of its wafer-scale systems for training and inference workloads.
Public Company Profile
Cerebras Systems Inc. trades on NASDAQ under the symbol CBRS. SEC filings identify the company as a Delaware corporation with principal executive offices in Sunnyvale, California. The company became public in connection with an initial public offering, and its filings include public-company governance documents, quarterly reports, equity incentive plan information, customer warrant disclosures, and material event reports.
As a public operating company, Cerebras reports through SEC forms that show how its business is structured and how its commercial relationships affect its financial statements. Recent filings discuss revenue recognition, deferred revenue, significant customers, investments, inventory reserves, product warranty provisions, stock-based compensation plans, and customer warrant assets. These disclosures are important because they show how Cerebras’ AI infrastructure business appears in formal regulatory reporting, beyond product and partnership announcements.
Frequently Asked Questions
Cerebras Systems investment returns
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