- NVIDIA’s GeForce RTX 40 GPU series surpasses laptop CPUs and dedicated NPUs in AI benchmarks.
- Performance is further boosted by TensorRT-LLM acceleration technology.
- The flagship GeForce RTX 4090 leads the pack with unprecedented speed and efficiency.
- RTX GPUs offer up to 48 GB of VRAM, ideal for handling LLM workloads.
- Benchmarks reveal significant performance differentials between RTX GPUs and laptop CPUs.
- External GPU configurations showcase even greater performance gains.
- NVIDIA solidifies its position as a leader in AI innovation.
Main AI News:
In a groundbreaking development, NVIDIA’s GeForce RTX 40 GPU series has set a new benchmark, outperforming both laptop CPUs and dedicated NPUs in Llama and Mistral AI benchmarks. This significant leap in performance is further amplified by NVIDIA’s TensorRT-LLM acceleration technology, heralding a new era of efficiency and speed in AI computing.
NVIDIA’s commitment to pushing boundaries is evident in the latest addition to its RTX “AI PC” platform – the GeForce RTX 4090 flagship GPU. Recent findings showcased in NVIDIA’s AI Decoded blog highlight the superiority of their current generation GPU over the entire NPU ecosystem. While NPUs struggle to reach 50 TOPS in 2024, NVIDIA’s RTX AI GPUs soar past with several hundred TOPS, peaking at an astonishing 1321 TOPS with the GeForce RTX 4090. Not only does this make it the fastest desktop AI solution for executing LLMs and other applications, but it also solidifies its position as the world’s fastest gaming graphics card.
With up to 24 GB of VRAM in GeForce RTX GPUs and up to 48 GB in NVIDIA RTX GPUs, these devices are tailor-made for handling the demands of LLMs. But it’s not just about memory capacity; NVIDIA’s RTX hardware boasts dedicated video memory and AI-specific acceleration through Tensor Cores, coupled with the game-changing TensorRT-LLM software.
Benchmarks conducted using the open-source Jan.ai platform, integrated with TensorRT-LLM, have revealed staggering performance differentials between NVIDIA’s GeForce RTX 40 GPUs and laptop CPUs equipped with dedicated AI NPUs. The RTX 4090 GPU, for instance, showcases an 8.7x improvement over the AMD Ryzen 9 8945HS CPU without TensorRT-LLM. When acceleration is enabled, this lead balloons to 15x, marking a monumental 70% increase over the non-TensorRT-LLM configuration. In practical terms, the RTX 4090 can process up to 170.63 tokens per second, leaving the AMD CPU in the dust at a mere 11.57 tokens/second. Even the NVIDIA GeForce RTX 4070 laptop GPU boasts an impressive acceleration of up to 4.45 times.
Not content with internal performance enhancements alone, NVIDIA has explored the realm of external GPU configurations. Benchmarks featuring an RTX 4090 in an eGPU setup have demonstrated a staggering 9.07x performance boost over an equivalent AMD laptop CPU. Once again, NVIDIA asserts its dominance in the AI landscape, offering unparalleled performance for AI applications and positioning the GeForce RTX 40 GPUs as the unequivocal choice for driving the next wave of AI innovation.
Conclusion:
NVIDIA’s groundbreaking advancements with the RTX 4090 GPU series herald a new era in AI computing, offering unmatched performance and efficiency. This development underscores NVIDIA’s dominance in the market, positioning them as the go-to choice for driving the future of AI innovation. Businesses and researchers alike stand to benefit from these cutting-edge technologies, unlocking new possibilities and pushing the boundaries of what’s achievable in AI-driven applications.
