InferenceMAX v1, a new benchmark from SemiAnalysis released Monday, is the latest to highlight Blackwell’s inference leadership. It runs popular models across leading platforms, measures performance for a wide range of use cases and publishes results anyone can verify. Why do benchmarks like this matter? Because modern AI isn’t just about raw speed — it’s about efficiency and economics at scale. As models shift from one-shot replies to multistep reasoning and tool use, they generate far more tokens per query, dramatically increasing compute demands. NVIDIA’s open-source collaborations with Ope
Telecommunications ArchivesBlackwell’s leadership comes from extreme hardware-software codesign. It’s a full-stack architecture built for speed, efficiency and scale: The Blackwell architecture features include: NVFP4 low-precision format for efficiency without loss of accuracy Fifth-generation NVIDIA NVLink that connects 72 Blackwell GPUs to act as one giant GPU NVLink Switch, which enables high concurrency through advanced tensor, expert and data parallel attention algorithms Annual hardware cadence plus continuous software optimization — NVIDIA has more than doubled Blackwell performance since launch using software
Telecommunications ArchivesAI is moving from pilots to AI factories — infrastructure that manufactures intelligence by turning data into tokens and decisions in real time. Open, frequently updated benchmarks help teams make informed platform choices, tune for cost per token, latency service-level agreements and utilization across changing workloads. Learn more about how to calculate lowest cost per token and how the NVIDIA Think SMART framework drives cost efficient inference.
Telecommunications ArchivesNVIDIA doubled Blackwell performance through continuous software optimization, refining kernels, compiler paths, and inference runtimes so the same hardware delivers significantly more useful AI throughput over time. Initial gpt-oss-120b performance on an NVIDIA DGX Blackwell B200 system with the NVIDIA TensorRT LLM library was market-leading, but NVIDIA’s teams and the community have significantly optimized TensorRT LLM for open-source large language models. The TensorRT LLM v1.0 release is a major breakthrough in making large AI models faster and more responsive for everyone. Through advance
Telecommunications Archives…To help expand AI expertise and enable diversity and resilience across the French AI ecosystem, AMD plans to provide researchers, developers and startups with hardware, software and training through its AMD University…
…This software-hardware integrated solution helps enterprises overcome GPU memory limitations and reduce AI deployment costs by more than 50% in model inference and fine-tuning scenarios. The launch also marks ADATA…
…AI hardware. This delivers real impact: lower TCO, better use of existing infrastructure, and AI that can be deployed in live networks today with no architectural overhaul. For operators exploring AI but…
…games hardware. In every other generation, the cost of a console has always gone down over time; for PS5, it's been the opposite. As Sony mentions, the "global economic landscape" is…
…resemble Walmart and Starbucks and more resemble the local hardware store or coffee shop. So far, much of the most intensive AI adoption has occurred at the enterprise level. In the recent…
…These pair with the NVIDIA NemoClaw reference stack and Dell Services to handle heavy AI workloads wherever they make the most economic sense. With Dell Deskside Agentic AI, organizations can reduce spend…
…The export control regime intended to slow China’s AI development instead hardened China’s self-sufficiency. Washington spent considerable political capital restricting China’s hardware access. DeepSeek answered in January 2024…
…A squeeze on components caused by AI companies, in addition to general economic headwinds – including tariffs introduced by the US government – has pushed the price of the PS5 Pro up to an…
…Zuhair's expertise lies in deconstructing complex topics such as fabrication nodes (e.g., 2nm process), the economic impact of policies like the CHIPS Act, and the strategic development of AI infrastructure…
Elon Musk’s SpaceX has highlighted AI as the tentpole of the company’s future, projecting a multi-trillion-dollar market opportunity that rivals the total value of all US economic activity…
