Can I Use a Second GPU for DLSS While Gaming on My RTX 4070?

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Asked By MellowCedar47 On

I currently have an RTX 4070 and recently repaired an RTX 3060 Ti that I found in a discarded PC. The 3060 Ti only needed a replacement cooler because its failed fan caused it to overheat and shut down.

My motherboard is an ASRock B550M Steel Legend, and I'm wondering whether I can install the 3060 Ti in the secondary PCIe slot using a riser cable. More importantly, could I have the RTX 4070 render the game while the RTX 3060 Ti handles DLSS, frame generation, or another part of the graphics workload?

3 Answers

Answered By CobaltNook31 On

The practical option is to keep the 4070 as the gaming card and use the 3060 Ti for a separate task, such as video encoding, extra monitors, CUDA applications, or experimenting with local AI software. Selling both and replacing them with one stronger card could also be simpler, but the second GPU won’t provide a straightforward DLSS upgrade for the 4070.

Answered By SilverPine29 On

You can probably connect the 3060 Ti to the lower PCIe slot with a suitable riser, assuming the slot, case space, power supply, and airflow are adequate. However, that only makes the card available to the system; it doesn’t make games automatically use it for upscaling or frame generation. The lower slot may also run at fewer PCIe lanes, though that usually matters more for workloads that constantly move data between the GPU and the rest of the system.

Answered By QuietMarble8 On

A second GPU generally won’t work this way for normal gaming. Modern games usually render and process features such as DLSS on the same GPU that is running the game. Traditional multi-GPU support was handled through technologies such as SLI, but that support has largely disappeared from current games. The extra card may be useful for compute, encoding, additional displays, or certain AI workloads, but it probably won’t accelerate DLSS on the 4070.

AmberQuill62 -

There are some specialized tools and game-specific setups that can split workloads between GPUs, but they aren’t a universal solution and often introduce compatibility or performance problems.

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