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Stable Diffusion XL on RTX 3050: Images/sec & VRAM Usage, Category: Benchmarks, Slug: sdxl-on-rtx-3050-benchmark, Excerpt: Stable Diffusion XL benchmarked on RTX 3050: 0.6 it/s, 1.2 images/min at 1024×1024, VRAM usage, and cost per 1K images., Internal links: 8 –>

Stable Diffusion XL benchmarked on RTX 3050: 0.6 it/s, 1.2 images/min at 1024x1024, VRAM usage, and cost per 1K images., Internal links: 8 -->

Stable Diffusion XL was built for 1024×1024 output, and the RTX 3050‘s 6 GB of VRAM is the bare minimum to make that happen. The result is functional but unhurried: about 50 seconds per image. We tested the boundaries on a GigaGPU dedicated server.

Generation Speed

MetricValue
Iterations/sec0.6 it/s
Seconds per image50.0 sec (30 steps)
Images per minute1.2
Resolution1024×1024
SamplerEuler a / DPM++ 2M Karras
Performance ratingGood

30-step generation at 1024×1024, batch size 1, FP16. Tested via A1111 WebUI and ComfyUI. One image every 50 seconds is slow for production, but perfectly usable for creative iteration where you are reviewing each output before generating the next.

VRAM Capacity

ComponentVRAM
Model weights5.5 GB
Sampling buffer~1.1 GB
Total RTX 3050 VRAM6 GB
Free headroom~0.5 GB

Half a gigabyte of headroom means the card is nearly maxed out. Stick to 1024×1024 or lower — attempting higher resolutions will crash or trigger aggressive tiling that tanks quality. Batch generation is not practical at this memory level either.

Cost Per Image

Cost MetricValue
Server cost£0.25/hr (£49/mo)
Cost per 1K images£3.47
Images per £1288

At £3.47 per thousand images, the 3050 is affordable in absolute terms. But the throughput bottleneck means you are generating just under 1,800 images per day at maximum utilisation. For higher-volume needs, the RTX 4060 more than doubles the pace. Compare all options in our benchmark tool.

Ideal Use Cases

The 3050 is a sensible SDXL choice for artists doing manual creative work, prototyping LoRA training outputs, or building a ComfyUI workflow before scaling it up. It is not the card for batch processing or API-served generation.

Quick start:

docker run --gpus all -p 7860:7860 ghcr.io/ai-dock/stable-diffusion-webui:latest

See the SDXL hosting guide, best GPU for Stable Diffusion, and full benchmark index. Related: Flux.1 hosting.

SDXL on the RTX 3050 — Entry-Level Image Gen

Lowest-cost path to 1024×1024 generation. UK datacentre, £49/mo flat, root access.

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We benchmark, deploy, and optimise GPU infrastructure for AI workloads. All data in our guides comes from real-world testing on our UK-based dedicated GPU servers.

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