Google battles Chinese open weights models with Gemma 4
… Alongside these models are a pair of LLMs optimized for low-end edge hardware like smartphones and single board computers, like the Raspberry Pi. …
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Unpacking the deceptively simple science of tokenomics
… The exact ratio of prefill GPUs to decode GPUs is going to vary from model to model and depend to some degree on your desired goodput. You might want fewer decode and more prefill GPUs if you're trying to serve lots of users. …
Nvidia slaps Groq into new LPX racks for faster AI response
… The GPUs will handle the compute-intensive prompt processing, while the LPUs spew out tokens. The GPU giant needs that many chips because, while SRAM may be fast, the chips are neither capacious nor compute-dense. …
A closer look at Nvidia's Groq-powered LPX rack systems
… The exact ratio of GPUs to LPUs depends on the workload. Tasks requiring extremely large contexts, batch sizes, or concurrency may need a larger pool of GPUs. …
Storage vendors orbit the Nvidia sun at GTC
… Hitachi iQ now supports: Nvidia Blackwell GPUs air-cooled Blackwell Ultra GPUs air-cooled and liquid-cooled Nvidia MGX-based system with up to four RTX PRO 6000 Blackwell Server Edition GPUs Hitachi iQ also plans to support the newly announced RTX PRO 4500 Blackwell Server Edition GPU Hitachi Vanta… …
Guide to GPU virtualization: passthrough, vGPU, and MIG
Systems A beginner's guide to GPU virtualization: passthrough, vGPU, and MIG What every IT generalist needs to know before deploying GPU workloads, and why the platform matters more than the hardware. …
The agentic AI boom is here; operations will decide who wins
… Together, this delivers higher GPU utilization, stronger isolation, and materially lower cost per token. …
Rebellions eyes global expansion with rack-scale AI platform
… Compared to GPU systems, this isn't a lot of networking. Most HGX systems now feature at least one 800 Gbps NIC per GPU. …
Inside datacenter where day starts with cerebrospinal fluid
… The CEO says they can do that faster than classical computers, create original ideas instead of regurgitating and re-ordering information like LLMs, and do it all while using less energy than conventional datacenters. …
The AI divide putting open weights models in spotlight
… It's a similar story with Qwen 3.5, where all but the two largest models would fit comfortably on a single GPU. In many cases, these smaller enterprise-focused models may not even need that much compute, Buss notes. "We don't often need things like GPU acceleration. …