Inference Archives
…for AI factories . A $5 million investment in an NVIDIA GB200 NVL72 system can generate $75 million in token revenue. That’s a 15x return on investment (ROI) — the new economics of…
Search
People also ask
How Did NVIDIA Double Blackwell Performance Through Continuous Software Optimizations to Lower Token Cost?
NVIDIA 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 ArchivesWhat Hardware-Software Innovations Power Blackwell’s Leadership?
Blackwell’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 ArchivesHow Is AI Shifting from Pilots to AI Factories and What’s Next?
AI 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 ArchivesWhat Is InferenceMAX v1 and Why Does It Matter for AI Economics?
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 ArchivesNemotron Archives
…for AI factories . A $5 million investment in an NVIDIA GB200 NVL72 system can generate $75 million in token revenue. That’s a 15x return on investment (ROI) — the new economics of…
NVIDIA and Partners Showcase the Future of AI-Driven Manufacturing at Hannover Messe 2026
…Bringing AI Agents to the Factory Floor Traditional AI answers problems under a rigid set of conditions. AI agents bring a new level of proactive and adaptive intelligence that provides the context…
NVIDIA Research Unlocks Advanced Grasping, Smarter Autonomous Driving and Agent Training at Scale
…They generated 2 billion simulated grasps across thousands of object shapes and synthetic gripper configurations, spanning the diversity of form factors a deployed robot might encounter. For robot developers, this foundation model…
For Robotaxis, Safety Must Be Built In, Not Bolted On
…Standardized and Safe Interfaces A robotaxi integrates cameras, radar, lidar and other sensors, each streaming data in a different format at a different rate. Without a standardized middleware layer, every hardware change…
NVIDIA GTC 2026: Live Updates on What’s Next in AI
…Together, the Feynman generation advances every pillar of the AI factory: compute, memory, storage, networking and security. And to help accelerate the scale-out of new AI capacity, Huang announced the NVIDIA…
NVIDIA Levels Up Local AI Agents Across RTX PCs and DGX Spark
…NVIDIA Factory Operations Blueprint Gives Factories a New AI Brain May 31, 2026 NVIDIA Research Advances Robotics From Simulation to the Real World May 28, 2026 Into the Omniverse: Manufacturing’s Simulation…
NVIDIA Accelerates Google DeepMind’s DiffusionGemma for Local AI
The new DiffusionGemma open model generates text in parallel — not one token at a time — and is optimized to run on the NVIDIA RTX PRO platform, NVIDIA DGX Spark systems and GeForce…
What’s the Difference Between Deep Learning Training and Inference?
…the web and more — in the streamlined form of an application. This speedier and more efficient version of a neural network infers things about new data it’s presented with based on…
To show you the most relevant results, we’ve omitted some entries very similar to those already shown. Repeat the search with the omitted results included.