Cerebras Systems Inc. · Q2 2026 call

As we've shared with you previously, 2026 is a foundation-building year for Cerebras. We've made excellent progress on multiple fronts in the past seven weeks since our last earnings call, preparing us for a massive 2027, 2028, and 2029 as we deliver on the $25 billion of RPO we currently have on our books. With the benefit of that progress, we expect to more than triple our core revenues in 2027 and continue to grow at multiples in the years following.

On the capacity front, data center space continues to be the bottleneck for the entire industry, and we are no exception. The faster we and our customers bring on new data centers, the faster we grow.

We now have data centers either up or under contract in Alabama, Dallas, Denver, Minneapolis, Santa Clara, Stockton, and outside the U.S. in France, Finland, Manitoba, Montreal, Norway, Saskatchewan, and Toronto. In total, over the last seven months, we have secured more than 600 MW of data center capacity that is either live now or will be delivered by the end of 2027. While this is not nearly enough to meet our demand, our data center pipeline of new opportunities for expansion continues to grow and is now measured in gigawatts.

Finally, recall that most of the critical supply chain constraints currently faced by the industry don't apply to us. For example, we don't use HBM memory, CoWoS packaging, or require 3 nm fab capacity.

Our collaboration on serving models at the frontier has opened up new and significant strategic advantage previously only available to NVIDIA. Closed-source frontier models include a continual stream of new insights and new AI techniques. Serving these models allows us to see into the future and to prepare for it.

GPU solutions can support high throughput, but only at low speeds. When configured to support even moderate speeds, GPU throughput drops precipitously. This is true not just for GPUs, but also for ASICs and all solutions that use HBM. The HBM memory architecture forces a trade-off between throughput and speed. SRAM-based architectures like Cerebras' are the exact opposite. We support blisteringly fast tokens, but at moderate throughput.

Increasing throughput by 5x while keeping our industry-leading speed has a profound impact on the economics of token generation. It means up to 5 times as many high-speed, high-value tokens are made by each Cerebras system. More tokens per system at lower cost means more revenue and more gross margin.

With all of this progress, I think it's important to keep in mind that our $25 billion in RPO does not reflect any backlog of business from AWS or any other hyperscaler at this time.

For example, in Q2, we signed six deals north of $30 million. AI coding continues its rapid rate of growth. In our experience, no one says, "I'm happy with slow tokens" when coding.

Second, we needed to scale our manufacturing capacity. We are already 4 times above where we were in the first half of 2025, and we will have increased the manufacturing capacity more than 10x in 2026.

Core revenue was $209.9 million, up 103% year-over-year. Our private cloud business is growing at an extraordinary pace. Core cloud and other services revenue was $127.7 million, up 287% year-over-year. This nearly fourfold increase reflects the tremendous demand we have for Cerebras' Fast Inference service. Core hardware revenue was $82.1 million in the quarter, up 17% compared to last year.

As we described last quarter, we are meeting some of the overwhelming demand for our fast inference service by temporarily renting some of our own systems back from our cloud customers and making it available through the Cerebras cloud. […] In the short term, it reduces gross margin as we have a higher cost for this rented capacity. As a result, sequentially, core gross margin was 40.6% versus 46.5% in Q1 2026. Had we not had higher costs due to increasing our private cloud capacity by renting back more of our systems, core gross margins would have been approximately 500 basis points higher and more similar to last quarter.

Looking forward, we expect Q3 to be the low point for core gross margin before improving significantly in Q4 2026 as we bring on more data centers filled with lower-cost Cerebras owned systems. This will cause core cloud gross margin to step back up. Core gross margin will also continue to improve in 2027 and trend towards our target of 60% plus for several reasons.

Core operating loss was $33.6 million. Core operating margin was negative 16% compared to negative 42% a year ago, an improvement of approximately 2,600 basis points year-over-year. Our ability to deliver this significant improvement in core operating margin while more than doubling revenues and stepping up our investments in all areas demonstrates the strong operating leverage inherent in our business model.

We ended Q2 with more than $8.6 billion in cash equivalents, restricted cash, and marketable securities. We also have a revolving credit facility of up to $850 million that has been unused to date.

In addition, we have the advantage of much lower net capital expenditures per megawatt than the vast majority of AI cloud providers for two key reasons. First, we primarily incur CapEx for the deployment of our own hardware and our data centers at much lower BOM cost that does not include the high profit margins many others must pay. Second, we are reimbursed for a meaningful portion of the remaining CapEx for data center fit-out as data center pass-through cost reimbursement from our largest customer.

For Q3 2026, we expect core revenue to be in the range of $214 million-$216 million, core gross margin in the range of 38%-40%, and core operating margin in the range of -25% to -23%. For the full year 2026, we are raising core revenue to the range of $880 million-$890 million. We are raising core gross margin to the range of 41%-43%, and we are raising core operating margin to the range of -19% to -17%.

Today, Cerebras is one of only four companies, Google, Amazon, NVIDIA, and Cerebras, to build processors, systems, data centers, and deliver AI-based cloud services to customers.

In 2021, people complained that we only had government customers. Then when we won a sovereign cloud at $1 billion, there were concerns we only had a sovereign cloud. Then we won the largest frontier lab, and then there were concerns that we didn't have a hyperscaler, and then we won AWS. […] I think OpenAI is an enormous customer, and they're an enormous part of not just our business, but of everybody's business in the sector. I think they'll stay a big part next year.