Executive Vice President and Chief Financial Officer at NVIDIA
Thanks, Jensen. Moving to Data Center, record revenue of $3.3 billion grew on 11% sequentially and 71% from a year earlier. Fiscal year revenue of $10.6 billion was up 58%. Data Center growth in the quarter was once again led by our compute products on strong demand for NVIDIA AI. Hyperscale and cloud demand was outstanding with revenue more than doubling year-on-year. Vertical industries also posted strong double-digit year-on-year growth, led by consumer Internet companies. The flagship NVIDIA A100 GPU continue to drive strong growth. Inference focused revenue more than tripled year-on-year. Accelerating inference growth has been enabled by widespread adoption our Triton Inference Server software, which helps customers deliver fast and scalable AI in production. Data Center compute demand was driven by continued deployment of our Ampere architecture based products for fast growing AI workloads such as natural language processing and deep learning recommendation systems as well as cloud computing.
For example, Block Inc, the global leader in payment uses conversational AI in its square assistant to schedule appointments with customers. These AI models are trained on NVIDIA GPUs and AWS and perform inference 10x faster on the AWS GPU servers and on our CPUs. Social media companies Snap used NVIDIA GPUs and Merlin, deep recommend daters software to improve inference cost efficiency by 50% and decreased latency by 2x. For the third row -- year in a row, industry benchmark show that NVIDIA AI continues to lead the industry and performance along with partners like Microsoft Azure, NVIDIA set records in the latest MLPerf benchmarks for AI training across eight popular AI workloads including computer vision, natural language processing, recommendation systems, reinforcement learning and our chip detection.
NVIDIA AI was the only platform to make submissions across all benchmarks and use cases, demonstrating the totality as well as our performance. The numbers show performance gains on our A100 GPUs of over 5x in just 18 months, thanks to continuous innovations across the full stack in AI algorithms, optimization tools and system software. Over the past three years performance gains of over 20x powered by advances we have made across our full stack offering GPUs, networks, systems and software. The leading performance of NVIDIA AI is sought after by some of the worlds most technically advanced companies by the platforms unveiled its new AI super computer Research SuperCluster with over 6,000 A100 GPUs led to an NVIDIA quantum. Net of all these benchmarks showed a system can train large natural language process model 3x faster and run a computer vision jobs 20x faster than the prior system.
In a second phase later this year the system will expand to 16,000 GPUs, and will deliver 5x of mixed precision AI performance. In addition to performance and scale, Meta hided extreme reliability, security, privacy and flexibility to handle a wide range of AI models as its key criteria for the system. We continue to broaden the reach and we use the adoption of NVIDIA AI in two vertical industries. Our ecosystem of NVIDIA certified systems expanded with Cisco and Hitachi antenna which joined Dell, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro among other several manufacturers. We released version 1.1 of our NVIDIA AI enterprise software allowing enterprises to run accelerated AI workloads on NVIDIA on mainstream IT infrastructure as well and we expanded a number of system integrators qualified for NVIDIA AI enterprise.
Forrester Research and its evaluation of vendor project AI infrastructure providers recognized NVIDIA the top category of gaming. An example of a partner that's helping to expand our reach into enterprise IT is Deloitte, a leading global consulting firm which is built its center for AI computing on NVIDIA DGX super comps. At CES, we extended our collaboration to AV development leveraging our robust AI infrastructure and Deloitte's team of 5,500 system integration developers and 2000 data scientists to architect solutions or truly intelligent transportation. Our networking products puts a strong sequential and year-over-year growth driven by exceptional demand across use cases ranging from our computing, super computing enterprise.
These not adopters led growth driven by the adoption of our next-generation products and higher speed departments. Our revenue was gated by supply we anticipate improving capacity in coming quarters that should allow us to serve the significant customer demand we're seeing. Across the board we are excited about the traction we are seeing with our new software business models, including NVIDIA AI, NVIDIA Omniverse and NVIDIA DRIVE. We are still early in the software revenue ramp, our pipelines are building customers across the industries seek to accelerate the pace of adoption and innovation with NVIDIA.
Now, let me turn it back over to Jensen for some comments.