For years, enthusiasts and professionals have relied on multi-GPU technologies to push the boundaries of graphics performance. Nvidia has pioneered much of this innovation with solutions like SLI and, more recently, NVLink. While both technologies allow multiple GPUs to work together, their technical approaches and ideal use cases differ dramatically. This article explores the key differences between Nvidia’s SLI (Scalable Link Interface) and NVLink, helping users understand which solution fits their performance and scalability needs.
Understanding the Basics of SLI and NVLink
SLI was introduced by Nvidia in 2004 with the intent of allowing two or more graphics cards to share rendering workloads. SLI functions by linking GPUs with a physical bridge connector, enabling them to split frame rendering tasks in a game or application. Despite its promising start, SLI has gradually fallen out of favor due to a lack of software support and diminishing returns as game engines and drivers moved away from multi-GPU rendering.
On the other hand, NVLink is Nvidia’s high-speed interconnect, introduced with the Pascal architecture and significantly advanced with Volta, Turing, and Ampere GPUs. It extends beyond SLI’s capabilities, offering faster data transfer rates and a more integrated memory model. NVLink is designed not only for gaming but also for compute-intensive workloads like AI, deep learning, and simulations.
Performance and Bandwidth Differences
One of the most significant differentiators between NVLink and SLI is bandwidth capacity.
- SLI: The SLI bridge used with high-end cards like the GTX 1080 and earlier could provide up to 2 GB/s of bandwidth. For most gaming use cases at the time, this was sufficient. However, performance issues emerged at higher resolutions and with more graphically complex tasks.
- NVLink: The first generation of NVLink provided around 20 GB/s per link, with modern implementations surpassing 50 GB/s, depending on the GPU architecture. This massive increase in bandwidth significantly reduces latency and enables better utilization of shared GPU memory.
Thanks to its high bandwidth, NVLink allows for more seamless data sharing between GPUs, making it highly effective for parallel computing tasks and large-scale simulations where memory bottlenecks can otherwise be significant.
Use Case Scenarios
While both technologies connect multiple GPUs, the ideal environments for their use have diverged considerably.
- SLI: Primarily designed with consumer applications in mind, SLI was most effective in gaming scenarios. However, in recent years, game developers have phased out native multi-GPU support, due to complexity and poor performance scaling. Today, very few modern titles support SLI reliably, making it a less viable option even for enthusiast gamers.
- NVLink: Targeted toward data centers, AI research, and high-performance computing (HPC), NVLink shines in professional applications. It is used extensively in Nvidia’s high-end products like the A100, Tesla, and even in RTX professional GPUs, allowing multiple GPUs to function as a unified processor with shared memory and ultra-fast interconnect speeds.
Hardware and Software Support
Another area where the differences are evident is in platform and software support.
- SLI: Only supported on select Nvidia consumer GPUs, with support increasingly limited in newer driver revisions. As of the RTX 3000 series and beyond, Nvidia has officially ended SLI support for most cards, relegating multi-GPU performance to applications that use alternative APIs like DirectX 12 or Vulkan with explicit multi-GPU programming.
- NVLink: Supported across Nvidia’s professional hardware lineup and integrated into their CUDA programming model. Developers can leverage this support to optimize applications for multi-GPU computing under Nvidia’s software ecosystem, making it a preferred choice in industries requiring massive compute power.
Conclusion: NVLink as the Future of GPU Interconnects
While SLI served as a stepping stone in the evolution of multi-GPU rendering, its limitations in bandwidth and driver support have rendered it nearly obsolete in today’s computing landscape. NVLink—equipped with significantly higher data throughput and a broader application in compute-intensive industries—has effectively taken its place as the modern solution for GPU interconnects.
For gamers, the era of multi-GPU setups is effectively over, but for scientists, developers, and AI researchers, NVLink represents a key technology enabling scalable, high-performance computing.
