Jalapeño (OpenAI chip)

Jalapeño is a custom AI accelerator designed by OpenAI with silicon implementation and networking technology from Broadcom. The companies unveiled it on June 24, 2026 as OpenAI's first "Intelligence Processor" and the first chip in a planned multi-generation compute platform. It is designed specifically for large language model inference rather than as a general-purpose training accelerator.^[1][2]

At launch, Jalapeño was not deployed at scale. Engineering samples were running machine-learning workloads in OpenAI's laboratory at the intended production frequency and power, but OpenAI was still measuring final performance. Initial deployment was targeted for the end of 2026. No process node, memory specification, peak throughput, power figure, price, or independently reproduced benchmark had been published by July 24, 2026.^[1][5]

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Identity and launch status

OpenAI's published name for the chip is simply Jalapeño. "Intelligence Processor" is the company's product category for it, not a disclosed architectural standard. The launch followed the October 2025 announcement of the broader OpenAI-Broadcom accelerator program, which covers multiple chip generations, network systems, and a long-term deployment plan.^[1][3]

The June announcement showed that the first design had advanced beyond simulation. OpenAI said engineering samples were running at target frequency and target power, including a GPT-5.3-Codex-Spark workload. Target settings do not establish production readiness by themselves: the companies did not disclose the number of samples, manufacturing yield, clock frequency, power draw, duration of testing, or reliability results.^[1][2]

OpenAI and Broadcom say Jalapeño moved from initial design to manufacturing tape-out in nine months. OpenAI models assisted parts of the design and optimization process. The companies described this as possibly the fastest development cycle for a high-performance application-specific chip, but did not publish a comparison set or independent evidence for that superlative. Tape-out means the design package was completed for manufacture; it is not the same milestone as volume deployment.^[1][2]

Inference workload

Jalapeño is a blank-slate design for LLM inference. Inference is the phase in which a trained model processes a request and produces an output. OpenAI says it shaped the hardware around the kernels, memory movement, networking, scheduling, and serving patterns used by its products. Named workloads include ChatGPT, OpenAI Codex, the OpenAI API, and future agentic products.^[1]

The design goal is to combine the power and throughput of leading AI accelerators with latency closer to specialized inference systems. OpenAI also says the architecture reduces data movement and balances compute, memory, and networking resources so that useful performance can remain closer to theoretical peak. These statements describe the intended system behavior. The launch did not include measurements needed to test the claims.^[1][8]

Although OpenAI designed the chip around its own operating experience, it says Jalapeño is flexible enough to run current and future LLMs across the industry. That compatibility claim does not mean the chip is a merchant product. Reuters reported that Jalapeño chips and their associated server systems would be used only by OpenAI.^[5]

Design and production roles

OpenAI owns the accelerator architecture. It says the design reflects its model roadmap, inference kernels, serving software, and product needs. Broadcom contributed silicon implementation and the networking and connectivity technologies required to turn that architecture into a production system. Celestica supplies board, rack, and system expertise, and Reuters reported that Celestica would build the server systems.^[1][5]

Broadcom specifically names Tomahawk networking silicon as part of the surrounding platform. The launch material does not identify a Tomahawk generation, network topology, link rate, or per-rack configuration. The earlier program announcement says the planned racks use Broadcom Ethernet for both scale-up and scale-out, together with Broadcom PCIe and optical connectivity. That program-level description does not provide the detailed fabric specification for the first Jalapeño system.^[1][3]

Reuters reported that OpenAI sent the completed design to TSMC for manufacturing. Neither OpenAI nor Broadcom named the semiconductor process node in the product announcement. Broadcom's Form 10-Q for the quarter ended May 3, 2026 says that TSMC produced about 95% of the wafers made by Broadcom's contract manufacturers across the company. This company-wide figure does not identify Jalapeño's node, allocated wafer volume, packaging line, or yield.^[5][7]

Performance claims and missing evidence

OpenAI says early internal testing indicates substantially better performance per watt than current state-of-the-art hardware. It also says important workloads can execute close to the chip's theoretical limits. The company promised a detailed performance report in the following months, but no Jalapeño technical report was found by July 24, 2026.^[1]

Broadcom CEO Hock Tan told Reuters that the chip was as good as Nvidia Blackwell or Google tensor processing units. The comparison did not identify a specific chip, model, precision, batch size, sequence length, software stack, latency target, or power boundary. It therefore cannot be converted into a quantitative performance result.^[5]

Axios reported another vendor claim that sample-chip thermal behavior was better than expected. The report also lacked temperatures, cooling conditions, power readings, or a baseline. None of these launch statements is an independent benchmark.^[6]

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The absence of public numbers prevents a fair comparison with GPUs, tensor processors, or other inference accelerators. It also prevents claims about cost per token or energy savings in production.

Technical specifications not disclosed

OpenAI and Broadcom did not publish a conventional datasheet. As of July 24, 2026, the following remained undisclosed:

• Process node and transistor count.
• Die area and chiplet organization.
• Package technology.
• Memory generation, capacity, stack count, and bandwidth.
• Supported numerical formats and sparsity modes.
• Peak compute throughput.
• Clock frequency and power draw.
• Chip-to-chip and network link rates.
• Accelerators per board or rack.
• Sample count, yield, production volume, and unit cost.

Launch photographs prompted third-party estimates of package details. Tom's Hardware explicitly treated its visual analysis as speculative and said the photographs could not establish the internal compute datapath. Other outlets produced different memory-stack counts from the same images. These estimates are not disclosed Jalapeño specifications and should not be used as such.^[8]

Reuters reported that Broadcom buys high-bandwidth memory from SK Hynix and Samsung for its custom-chip business. The report did not assign a particular memory generation, supplier, capacity, or stack count to Jalapeño, so those company-level supply relationships do not establish this chip's memory configuration.^[5]

Relationship to the 10 GW program

OpenAI and Broadcom announced a multi-year plan in October 2025 to deploy 10 gigawatts of OpenAI-designed custom accelerators and associated network systems. The plan calls for racks to begin deployment in the second half of 2026 and for the program to reach its target by the end of 2029. The systems are intended for OpenAI facilities and partner data centers and use Broadcom Ethernet and other connectivity products.^[3][4]

Jalapeño is the first accelerator in that multi-generation platform. The 10 GW figure applies to the full program, not necessarily to first-generation Jalapeño alone. Later accelerator generations can account for an unspecified part of the capacity. The companies did not disclose the number of chips represented by 10 GW, and electrical capacity cannot be converted into a device count without rack power and configuration data.^[1][3]

The June 2026 launch set a narrower target of initial Jalapeño deployment by the end of 2026, followed by expansion in later years. Broadcom said gigawatt-scale data centers with Microsoft and other partners would begin deployment in 2026. That wording identifies data center partners, not buyers of generally available Jalapeño hardware.^[1][2]

Deployment and commercialization

Axios reported that the first chips were expected to enter commercial use by the end of 2026, with the main volume arriving in 2027. At the announcement, however, only laboratory engineering samples were confirmed. The late-2026 date was a target rather than a completed deployment.^[1][6]

Reuters said the chips and Celestica-built server systems would be used only by OpenAI. No price, board, server product, licensing program, developer kit, or public-cloud instance was announced. There was also no announcement that Microsoft or another hosting partner would offer the accelerator to its own customers. Jalapeño is therefore best described as internal OpenAI infrastructure that can be installed in partner data centers, not as a generally purchasable Broadcom accelerator.^[5]

The financial terms of the OpenAI-Broadcom program were not disclosed. The October 2025 announcement referred to existing co-development and supply agreements and a term sheet for rack deployment, but it did not publish purchase commitments, per-chip prices, or financing terms.^[3][4]

Limitations and rollout risks

Broadcom's investor release classifies its large-scale production and deployment statements as forward-looking. It identifies risks involving demand timing, contract manufacturing, limited suppliers, manufacturing capacity and quality, regulation, trade restrictions, and customer financing. Those cautions apply to the rollout plan; they are not evidence that Jalapeño has suffered a particular defect or delay.^[2]

Broadcom's May 2026 Form 10-Q likewise describes company-wide dependence on a small number of contract manufacturers and materials suppliers. It warns that complex semiconductor products can face delays, defects, yield problems, and capacity constraints. The filing does not name Jalapeño or disclose its contract, node, order volume, or production economics.^[7]

The central limitation at launch is the difference between a running sample and a proven production platform. OpenAI had demonstrated lab workloads at target settings, but had not published numeric performance, power, memory, reliability, yield, or rack-scale results. The initial deployment schedule, performance-per-watt advantage, and later gigawatt expansion remain claims to verify against the promised technical report and production evidence.^[1][2]

References

1. OpenAI, "OpenAI and Broadcom Unveil LLM-Optimized Inference Chip," June 24, 2026. https://openai.com/index/openai-broadcom-jalapeno-inference-chip/ ↩
2. Broadcom, "OpenAI and Broadcom Unveil LLM-Optimized Intelligence Processor," June 24, 2026. https://www.globenewswire.com/news-release/2026/06/24/3316887/19933/en/openai-and-broadcom-unveil-llm-optimized-intelligence-processor.html ↩
3. OpenAI, "OpenAI and Broadcom Announce Strategic Collaboration to Deploy 10 Gigawatts of OpenAI-Designed AI Accelerators," October 13, 2025. https://openai.com/index/openai-and-broadcom-announce-strategic-collaboration/ ↩
4. Broadcom, "OpenAI and Broadcom Announce Strategic Collaboration to Deploy 10 Gigawatts of OpenAI-Designed AI Accelerators," October 13, 2025. https://www.globenewswire.com/news-release/2025/10/13/3165560/0/en/OpenAI-and-Broadcom-announce-strategic-collaboration-to-deploy-10-gigawatts-of-OpenAI-designed-AI-accelerators.html ↩
5. Max A. Cherney, "OpenAI Unveils Custom Chip It Designed with Broadcom to Boost Its AI Infrastructure," Reuters, June 24, 2026. https://m.investing.com/news/stock-market-news/openai-unveils-custom-chip-it-designed-with-broadcom-to-boost-its-ai-infrastructure-4758233?ampMode=1 ↩
6. Ina Fried, "OpenAI Moves Beyond Nvidia," Axios, June 24, 2026. https://www.axios.com/2026/06/24/openai-jalapeno-ai-chip-broadcom-nvidia ↩
7. Broadcom, Form 10-Q for the Quarter Ended May 3, 2026, filed June 9, 2026. https://www.sec.gov/Archives/edgar/data/1730168/000173016826000054/avgo-20260503.htm ↩
8. Anton Shilov, "Broadcom and OpenAI Unveil Custom-Built Jalapeño Inference Processor," Tom's Hardware, June 24, 2026. https://www.tomshardware.com/tech-industry/artificial-intelligence/broadcom-and-openai-unveil-custom-built-jalapeno-inference-processor-openais-first-chip-is-a-massive-reticle-sized-asic-built-in-an-ultra-fast-nine-month-development-cycle ↩