High VRAM requirements. Latency sensitivity for interactive use. Throughput demands for batch asset pipelines. Match your deployment mode to the right GPU.
SDXL base needs 10GB+ at fp16 just for the UNet. Add ControlNet, LoRA adapters, and a VAE decode, and you're pushing 20GB. Flux.1 dev runs north of 24GB. Shared GPUs don't have room.
Generative APIs serving users in real-time need sub-2s end-to-end. Shared GPU contention adds unpredictable variance. Dedicated endpoints give you consistent generation time.
Asset pipelines — product images, synthetic datasets, creative workflows — care about images-per-hour at minimum cost. Spot pricing with async jobs is the right model here.
An always-on dedicated endpoint keeps your diffusion model loaded. No cold start, no VRAM eviction between requests. Generation time is predictable because it's yours.
Works with SDXL, Flux.1, ControlNet pipelines, img2img, inpainting, and any HuggingFace Diffusers-compatible model. Bring your own LoRA adapters.
Two-stage pipeline. L40S handles it comfortably. ~3s generation at 1024×1024.
24–32GB VRAM. L40S or A100. Schnell gives 4-step generation for interactive latency.
Add ControlNet on top of SDXL base. Needs 20GB+. A100 is the right call here.
Load your style or character LoRAs at startup. They stay resident — no per-request loading overhead.
Generating thousands of product images, synthetic training data, or creative variants doesn't need low interactive latency. It needs throughput and low cost per image.
Async batch jobs on spot instances. Output images write directly to your storage bucket. Cost drops 40–60% vs on-demand.
Video generation models (CogVideoX, Wan, AnimateDiff, Mochi) carry significantly higher VRAM requirements than image-only diffusion. Temporal attention alone pushes memory usage well above what a 24GB card can handle at useful resolutions.
For production video generation, treat H100 as the baseline. A100 80GB works for shorter clips or lower resolutions.
Video Model Reference
VRAM estimates at default precision. fp8 or INT8 quantization can reduce requirements.
Best $/image ratio for standard diffusion pipelines. Handles ControlNet and LoRA stacks comfortably.
Flux.1-dev needs A100 for comfortable throughput. Schnell runs on L40S with acceptable latency.
AnimateDiff, CogVideoX-2B, shorter Wan clips. A100 80GB is the minimum for useful video generation.
High-resolution video synthesis at usable generation speed. H100 NVLink bandwidth matters here.
Multiple LoRA adapters plus base model. A100 80GB gives the memory headroom.
Community tier. Great for testing pipelines at low cost before scaling to production GPU.
Interactive endpoint for real-time generation, or async batch jobs at spot pricing for large pipelines. Both available today.