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Home/Models & Labs
Models & Labs

NVIDIA and Google Cloud Boost AI Developer Community

NVIDIA Blog·May 19, 2026·high confidence

Why it matters

  • →NVIDIA and Google Cloud are providing essential resources for AI developers to enhance their skills and build advanced applications.
  • →The collaboration supports the development of production-ready AI applications, leveraging NVIDIA's and Google Cloud's technologies.
  • →This initiative emphasizes the importance of responsible AI development with tools like SynthID for content transparency.
NVIDIA and Google Cloud Boost AI Developer Community
©NVIDIA Blog

NVIDIA and Google Cloud are expanding their joint developer community, which now includes over 100,000 developers, with new resources and learning paths. These additions, announced at Google I/O, include a JAX library learning path for NVIDIA GPUs and a NVIDIA Dynamo codelab focused on inference optimizations. The collaboration aims to enhance AI development using NVIDIA's AI platform on Google Cloud, enabling developers to build production-ready applications. This partnership highlights the companies' commitment to advancing AI technology and supporting developers with the necessary tools and infrastructure.

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NVIDIA Wins COMPUTEX 2026 Best Choice Awards© NVIDIA Blog
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NVIDIA Wins COMPUTEX 2026 Best Choice Awards

NVIDIA has made a significant impact at COMPUTEX 2026, securing multiple Best Choice Awards for its innovations in AI and autonomous technology. The Vera Rubin NVL72 supercomputer stood out with its impressive scalability and energy efficiency, winning both a Golden Award and the Sustainable Tech Special Award. Meanwhile, the Jetson Thor platform and Alpamayo open platform were recognized for their advancements in edge AI and autonomous vehicle development, respectively. These awards highlight NVIDIA's continued leadership in pushing the boundaries of AI infrastructure and application, setting new standards for performance and sustainability.

NVIDIA Blog·May 21, 2026

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llama.cpp b9297 release enhances tensor support

The b9297 release of llama.cpp brings a notable enhancement with the introduction of NVFP4 MTP scale tensors, boosting its tensor processing capabilities. This update also integrates Qwen3.5 MTP tensors, which improves performance across a spectrum of hardware configurations, including Apple Silicon, Vulkan, and ROCm on Ubuntu, as well as CUDA on Windows. The release supports a wide array of architectures, from macOS to Linux and Windows, ensuring compatibility with both CPU and GPU setups. While there are no new model architectures, the inclusion of KleidiAI on Apple Silicon and ROCm 7.2 on Ubuntu highlights llama.cpp's commitment to optimizing for diverse environments. This update reinforces llama.cpp's role as a flexible inference runtime, catering to a broad range of hardware setups.

llama.cpp Releases·May 25, 2026
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llama.cpp b9309 release fixes integer overflows

The b9309 release of llama.cpp tackles significant integer overflow issues in its perplexity calculations, co-authored by Stanisław Szymczyk. This update is vital for enhancing the accuracy and reliability of the model's performance metrics, which are crucial for developers. By resolving these overflows, the release ensures that users can depend on precise data outputs. This fix is a testament to the ongoing efforts to improve the tool's robustness, allowing developers to trust the integrity of their AI computations. While it might seem like a minor adjustment, it plays a critical role in maintaining the tool's reliability.

llama.cpp Releases·May 25, 2026
OpenAI Achieves Math Breakthrough© The AI Daily Brief
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OpenAI Achieves Math Breakthrough

OpenAI has made a significant advancement in mathematical capabilities within its AI models.

The AI Daily Brief·May 24, 2026