OpenAI has announced a collaboration with Broadcom to develop a custom inference chip named Jalapeño. This new hardware is designed specifically to accelerate the deployment of large language models. The partnership aims to reduce reliance on third-party accelerators for OpenAI's inference workloads. By integrating custom silicon, OpenAI seeks to optimize performance and efficiency for its AI applications. The announcement highlights a strategic move towards vertical integration in AI infrastructure. Details regarding specific technical specifications or release timelines were not provided in the initial report.
OpenAI and Broadcom Announce Jalapeño Inference Chip
OpenAI joins PORTS-Pike project
OpenAI has entered into an agreement to secure approximately 8 gigawatts-IT at the PORTS-Pike Technology Campus in Pike County, Ohio, in partnership with SB Energy, NVIDIA, and the U.S. Department of Energy.
NVIDIA serves Qwen 3.8 2.4T on GB300 NVL72 at 4K tokens/s per GPU
NVIDIA has demonstrated serving the Qwen 3.8 2.4T parameter model with configurable reasoning capabilities on its GB300 NVL72 hardware platform.
OpenAI Python SDK v0.21.0 adds provider-neutral testing APIs and OpenAI v3 compatibility
OpenAI released version 0.21.0 of the openai-agents-python SDK, introducing new provider-neutral testing utilities and updating compatibility for the OpenAI Python library version 3.
OpenAI previews GPT-5.6 Sol Ultrafast mode; Google releases Gemini 3.7 Flash
OpenAI has previewed Ultrafast, a GPT-5.6 Sol mode capable of generating up to 750 output tokens per second and operating at up to 14x standard processing speed. The approach aims to deliver real-time performance without switching to a smaller model.
Google releases Gemini 3.7 Flash; DeepSeek open-sources Harness
Google shipped Gemini 3.7 Flash, its new mid-tier model for coding and agentic workflows, featuring a 50% introductory price cut and significant benchmark gains over version 3.6. The release positions the model as a workhorse for development, with immediate integration across the Gemini API, Android Studio, and external tooling like Cline.