RTX 4070

RTX 4070 Specifications

The RTX 4070 is based on the Ada Lovelace architecture and manufactured using the 5 nm process node. It was launched approximately 2 years, 1 month ago, originally priced at $599. It features 5888 cores, including 28 compute units (SMs), 184 texture mapping units (TMUs), and 64 render output units (ROPs). For ray tracing and AI-accelerated tasks, it also includes 46 dedicated RT cores and 184 Tensor cores, enabling advanced rendering and upscaling features where supported. It has a base clock of 1920 MHz and a boost clock reaching up to 2475 MHz. The RTX 4070 comes equipped with 12 GB of GDDR6X memory across a 192-bit bus. Memory runs at 1313 MHz and delivers a total memory bandwidth of 504 GB/s.

This GPU has a low thermal design power (TDP) of 200 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 4070 Performance Review

RTX 4070 is a mid-range graphics card, scoring 51.39% in relative gaming performance. Thanks to 12 GB of VRAM, it offers excellent 1440p performance and can handle 4K gaming with optimized settings or the help of DLSS, FSR, and frame generation. Great for users targeting 100+ FPS at 1440p or playable 4K in lighter titles.

The RTX 4070 pairs a relatively powerful GPU core with a moderate VRAM size of 12 GB — a configuration that's becoming increasingly common. However, this pairing has sparked significant discussion in the gaming and tech review communities. Many modern GPUs with strong processing capabilities are equipped with insufficient VRAM (often less than 16 GB), which prevents them from realizing their full potential. As a result, GPUs like this one often deliver excellent performance in 1080p gaming at ultra settings, and perform well at 1440p in many titles. However, as modern games demand more VRAM — particularly due to high-resolution textures, ray tracing, and expansive open worlds — this limited memory becomes a bottleneck. In 4K gaming, performance can drop significantly due to VRAM exhaustion, leading to underutilization of the GPU core itself. Technologies such as DLSS or FSR can mitigate some of the performance loss at higher resolutions, but this often comes with a tradeoff in visual fidelity. This GPU configuration still handles basic to intermediate content creation tasks well — such as 1080p/1440p video editing, lightweight 3D modeling, and digital art workflows. For AI and machine learning applications, the GPU is capable of running small to mid-sized models and performing inference tasks. However, limited VRAM restricts its ability to handle larger models, which may require downsampling, reduced batch sizes, or precision reduction to run effectively.

With a 42.5% performance-per-price ratio, this GPU offers limited value. Its low VRAM and modest performance make it a poor long-term investment, especially with better alternatives available.