Broadcom Inc shares fell approximately 20% in June despite the company reporting record fiscal Q2 results and unveiling a new AI chip with OpenAI. The decline follows a revenue miss and investor concerns over the stock's premium valuation, overshadowing significant growth in its semiconductor business.

Record Q2 Earnings

Broadcom reported fiscal Q2 2026 revenue of $22.19 billion, a 48% increase year-over-year, though it missed the consensus estimate of $22.27 billion. Earnings per share of $2.44 beat the $2.40 consensus. AI semiconductor revenue surged 143% year-over-year to $10.8 billion, driven by demand for custom AI accelerators and AI networking.

The Jalapeño Reveal

On June 24, Broadcom and OpenAI unveiled Jalapeño, OpenAI's first custom AI inference chip. Broadcom handled the silicon implementation, networking, and connectivity technologies, while OpenAI designed the architecture. The chip moved from initial design to manufacturing tape-out in nine months. Early testing indicates performance per watt will be substantially better than current alternatives, with initial deployment targeted for the end of 2026.

Technical Analysis

Despite the recent pullback, Broadcom is holding above its 200-day moving average of $361.17. However, the stock is trading below its 20-day SMA of $406.77 and 50-day SMA of $412.60. The stock trades at a P/E of 63.0x, which remains a point of contention for investors.

Earnings & Analyst Outlook

The next major catalyst is the estimated earnings report on Sept. 3, 2026. Wall Street anticipates earnings per share of $3.16 on revenue of $29.43 billion. The stock maintains a Buy rating with an average price target of $513.68.

Broadcom Inc. and OpenAI unveiled Jalapeño, OpenAI’s first custom Intelligence Processor designed specifically for large language model (LLM) inference. Co-developed from initial design to manufacturing tape-out in nine months, the processor utilizes OpenAI models to optimize its design cycle. Engineering samples are currently running machine learning workloads, including GPT-5.3-Codex-Spark. Celestica Inc. assisted with board and rack system integration.

Custom Chip Development

The technical design of Jalapeño emphasizes minimizing data movement, a critical factor in improving overall system efficiency. By better integrating compute, memory, and networking resources, the processor seeks to maximize utilization rates. This approach is intended to bridge the gap between theoretical performance capabilities and actual realized performance in production environments. The architecture focuses on reducing data movement and balancing compute, memory, and networking resources to achieve realized utilization closer to theoretical peak performance.

Multi-Generation Infrastructure Roadmap

The hardware marks the first step in a multi-generation compute platform planned for initial deployment by the end of 2026. "By co-developing our industry-leading silicon directly with OpenAI, we are enabling the deployment of gigawatt-scale data centers with Microsoft and other partners beginning in 2026," Broadcom President and CEO Hock Tan stated.

Early testing indicates the chip delivers performance per watt substantially better than current state-of-the-art accelerators. "Based on early testing, Jalapeño will efficiently execute our most important workloads close to the hardware’s theoretical limits," said Richard Ho, leader of OpenAI’s hardware program.

Industry Context

Broadcom has quietly emerged as a key partner for hyperscalers and AI companies seeking specialized hardware tailored to specific workloads. Unlike NVIDIA, which sells its own accelerators, Broadcom’s opportunity lies in helping customers build theirs. The company’s role in the project includes providing silicon implementation and networking technologies, such as Tomahawk networking silicon, to facilitate the platform's large-scale production.

The shift toward custom silicon suggests the industry’s largest AI companies increasingly want hardware optimized for their own models and workloads rather than relying entirely on off-the-shelf chips. Alphabet Inc. has spent years developing its Tensor Processing Units, or TPUs. Amazon.com, Inc. built Trainium and Inferentia. Microsoft Corp introduced Maia. Meta Platforms, Inc. has been developing its own MTIA accelerators. Now OpenAI has joined the list.