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DLSS Transformer Update Boosts Quality, Cuts VRAM Use

DLSS Transformer Update Boosts Quality, Cuts VRAM Use

G
GAIAJuly 1, 2025
2 min read
Tech

Introduction

NVIDIA’s latest DLSS Super Resolution SDK 310.3.0 introduces transformer-based upscaling, aiming to free up GPU memory while delivering crisper images on GeForce cards.

Pros

  • Up to 20% less VRAM required at 4K and above
  • Sharper, more detailed frames thanks to transformer algorithms
  • Expanded compatibility across a wider range of GPUs

Cons

  • Still uses more memory than the original CNN model
  • Minor performance dip compared to earlier DLSS versions
  • No cure for extreme low-VRAM setups on budget cards

Verdict

Score: 8/10
For gamers hitting the VRAM ceiling—especially at 1440p+—this update offers tangible benefits. It won’t replace a hardware upgrade, but it’s a worthwhile quality‐of‐life boost for most GeForce owners.

FAQs & Community Insights

Will this update appear automatically?
DLSS SDK improvements arrive via driver and game patches. Developers must integrate support for “DLSS 3.5+ with transformer model” for players to see the change.
Should I stick with the CNN model on 8GB cards?
If you’re severely VRAM-limited (ultra textures at 4K), the older model still edges ahead in memory savings. For the majority, though, the visual upgrade outweighs the extra RAM cost.
Does it eliminate stutters in memory-heavy games?
It helps reduce stutter but isn’t a magic bullet—you’ll still need to watch texture and quality settings on lower-end cards.

The Bottom Line

This kind of under-the-hood tuning is exactly what I want to see more often from GPU makers. Transformer upscaling in DLSS SDK 310.3.0 delivers real-world improvements without just ticking a spec sheet box. Still, remember that the ultimate VRAM fix lies in the hardware itself—this update is a strong stopgap rather than a silver bullet.

Specifications

ModelNVIDIA DLSS SDK 310.3.0
Core TechnologyTransformer Upscaling
VRAM Usage (4K)307 MB (down from 387 MB)
Image QualitySignificantly improved over basic CNN
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