Okay, so this is actually exciting news for anyone who has been frustrated by the hardware requirements for running Stable Diffusion 3.5 locally. NVIDIA and Stability AI just dropped optimized TensorRT versions of SD 3.5, and the improvements are genuinely impressive.

Here's the deal: the original Stable Diffusion 3.5 Large model needed over 18GB of VRAM to run. That's a lot. Like, "you need a 4090 or a professional workstation GPU" a lot. Most of us don't have that kind of hardware sitting around. But with these new TensorRT optimizations? We're looking at 40% less memory usage, bringing the requirement down to around 11GB.

Let us talk real numbers because that's what matters. The SD 3.5 TensorRT-optimized models deliver up to 2.3x faster generation on the Large model and 1.7x faster on the Medium model. Combined with the memory savings, this opens up local SD 3.5 to five GeForce RTX 50 Series GPUs that couldn't run it before:

- RTX 5060 Ti (16GB)
- RTX 5070
- RTX 5070 Ti
- RTX 5080
- RTX 5090

And obviously, if you have got any of the higher-end RTX 40 series cards with 16GB or more VRAM, you're good to go too. The optimization also works across NVIDIA's RTX PRO line for the professional crowd.

How They Did It

The secret sauce here'sFP8 quantization combined with TensorRT optimization. By quantizing the model to FP8 precision, they managed to slash the VRAM footprint dramatically without destroying image quality. And TensorRT, which has been NVIDIA's AI inference optimization toolkit for a while now, has apparently been reimagined specifically for RTX AI PCs.

The new version features just-in-time engine building on your device, which means faster setup and an 8x smaller package size compared to previous versions.

Where To Get It

The optimized models are already available. You can grab the weights from Hugging Face - there's both a Large and Medium version. The code is up on NVIDIA's GitHub. And here's the nice part: they're released under the permissive Stability AI Community License, so you can use them for both commercial and non-commercial projects.

Should You Upgrade?

If you've been running SD 3.5 Medium because Large was too VRAM-hungry for your setup, this is definitely worth checking out. The 2.3x speed improvement on Large is substantial - that's the difference between waiting 30 seconds for an image versus waiting 13 seconds. When you're iterating on prompts and doing multiple generations, that time adds up fast.

And if you've been avoiding SD 3.5 entirely because your GPU couldn't handle it, now might be the time to give it a shot. The 11GB requirement is much more reasonable than 18GB+, and you get access to SD 3.5's improved text rendering, better coherence, and overall quality improvements over older versions.

The Catch

There's always a catch, right? In this case, you're still tied to NVIDIA hardware. If you're running an AMD GPU, these optimizations don't help you at all. TensorRT is NVIDIA-specific, so AMD users are stuck waiting for whatever optimizations come from that ecosystem.

Also worth noting: while 11GB is more accessible than 18GB, it's still not exactly entry-level. If you're running an RTX 3060 with 8GB, you're still out of luck for the Large model.

For more on running Stable Diffusion locally, see our Stable Diffusion guide.