NVIDIA just released the FLUX.1 Kontext [dev] NIM microservice, making advanced local image editing much easier on RTX PCs. Quantization slashes the 24GB model down to 7GB for RTX 50 series, while TensorRT delivers over 2x speedups with direct ComfyUI support.
NVIDIA just rolled out TensorRT optimizations for Black Forest Labs' FLUX.1 Kontext [dev] model, bringing over 2x faster image generation and editing to RTX GPUs. Quantization cuts model size down to 12GB for FP8 and 7GB for FP4, allowing creators to run step-by-step visual edits locally without complex workflows.
NVIDIA and Stability AI just introduced TensorRT FP8 optimizations for Stable Diffusion 3.5, slashing Large model VRAM needs from over 18GB down to 11GB while boosting performance by up to 2.3x. Developers can also grab the new standalone TensorRT for RTX SDK with JIT compilation. This basically puts heavyweight image generation within reach for standard consumer RTX rigs.
Stability AI just partnered with NVIDIA to optimize SDXL using TensorRT, releasing open ONNX weights globally. The integration doubles performance on NVIDIA H100 GPUs, spitting out HD images in 1.47 seconds with a 41% latency drop and 70% throughput jump. Why it matters: high-end open-source image generation just got significantly faster and cheaper to scale.
