RTX 2060 SUPER

RTX 2060 SUPER Specifications

The RTX 2060 SUPER is based on the Turing architecture and manufactured using the 12 nm process node. It was launched approximately 5 years, 11 months ago, originally priced at $399. It features 2176 cores, including 60 compute units (SMs), 136 texture mapping units (TMUs), and 64 render output units (ROPs). For ray tracing and AI-accelerated tasks, it also includes 34 dedicated RT cores and 272 Tensor cores, enabling advanced rendering and upscaling features where supported. It has a base clock of 1470 MHz and a boost clock reaching up to 1650 MHz. The RTX 2060 SUPER comes equipped with 8 GB of GDDR6 memory across a 256-bit bus. Memory runs at 1750 MHz and delivers a total memory bandwidth of 448 GB/s.

This GPU has a low thermal design power (TDP) of 175 W. It is generally compatible with almost all PC cases and is excellent for SFF and compact systems where heat dissipation is a concern.

RTX 2060 SUPER Performance Review

RTX 2060 SUPER is an entry-level graphics card with a relative gaming performance score of 26.62%. It performs well at 1080p and can handle 1440p with optimized settings or features like DLSS and FSR, though it's not suitable for 4K. Intended for for casual gamers or users who play occasionally on general-purpose PCs.

The RTX 2060 SUPER has a moderate VRAM size of 8 GB, which aligns well with its performance class. It is well-suited for 1080p gaming at high settings and 1440p gaming at medium to high settings, depending on the game’s optimization and graphics demands. While capable in rasterized workloads, enabling ray tracing at higher resolutions can quickly consume available VRAM and reduce performance. Upscaling technologies like DLSS or FSR can help improve frame rates, but may come with a noticeable reduction in visual quality. The VRAM capacity is adequate for light to moderate content creation tasks, such as editing Full HD or QHD video, working with smaller assets in 3D environments, and using tools like Photoshop or Premiere Pro for general workloads. In the context of AI and machine learning, this GPU can handle lightweight inference tasks and basic model training. However, users working with large datasets or complex architectures may find the memory insufficient, leading to slowdowns or compatibility issues. This GPU remains a good option for gamers, casual creators, and students exploring AI.

RTX 2060 SUPER provides excellent value at 76.3% efficiency. While its gaming performance is modest, it can still be a cost-effective solution for users with limited demands.