OpenAI Unveils First Custom AI Chip ‘Jalapeño’ to Deliver Faster LLM Inference, Power Next-Gen AI

OpenAI on Thursday unveiled its first custom-designed artificial intelligence (AI) accelerator called Jalapeño. It has been developed in collaboration with California-based semiconductor giant Broadcom. Instead of training, the San Francisco-based company describes it as an “Intelligence Processor” that is purpose-built for large language model (LLM) inference. It is claimed to deliver better performance per watt than current state-of-the-art solutions around compute, memory, and networking requirements.

Jalapeño and OpenAI's Long-Term Infrastructure Strategy 

The AI firm said that Jalapeño has been designed to handle inference workloads powering its services like ChatGPT, Codex, the OpenAI API, and future agentic AI products. This sets it apart from conventional AI accelerators that have been adapted from general-purpose architectures. All aspects of the chip, including its architecture, board layouts, rack integration, networking, and deployment systems, have been developed in collaboration with Broadcom and manufacturing partner Celestica.

As per the company, engineering samples of Jalapeño are already running machine learning (ML) workloads at production target frequencies and power levels in the company's labs, including GPT-5.3-Codex-Spark.

OpenAI claims the new AI accelerator can reduce data movement while balancing compute, memory, and networking resources to achieve utilisation much closer to the hardware's theoretical limits. However, performance figure benchmarks have yet to be revealed by the San Francisco-based AI startup.

Greg Brockman, President and Co-Founder of OpenAI, described Jalapeño as part of the company's effort to make AI faster, more reliable, and more affordable, stating that the world is rapidly moving towards a "compute-powered economy". The company expects Jalapeño to become the foundation of a multi-generation AI compute platform beginning next year.

Broadcom and OpenAI both claim that Jalapeño moved from the initial design stage to manufacturing tape-out in nine months. This is described as one of the fastest ASIC development cycles achieved for a high-performance AI semiconductor. The former contributed its silicon implementation expertise and high-speed networking technologies, such as its Tomahawk networking silicon, while the latter will help deploy the platform across large-scale AI data centres.

The introduction of the chip is a notable step in OpenAI's long-term infrastructure strategy of designing its own technology stack instead of relying entirely on third-party AI hardware.