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SD 1.5 on RTX 3050: Images/sec & VRAM Usage, Category: Benchmarks, Slug: sd-1.5-on-rtx-3050-benchmark, Excerpt: SD 1.5 benchmarked on RTX 3050: 2.8 it/s, 6.72 images/min at 512×512, VRAM usage, and cost per 1K images., Internal links: 8 –>

SD 1.5 benchmarked on RTX 3050: 2.8 it/s, 6.72 images/min at 512x512, VRAM usage, and cost per 1K images.

Stable Diffusion 1.5 remains the workhorse of AI image generation — smaller, faster, and more compatible with fine-tuned checkpoints than any successor. The question is: how low can you go on hardware? We ran SD 1.5 on the RTX 3050, the most affordable GPU in the GigaGPU lineup, to find the floor.

512×512 Generation Benchmarks

MetricValue
Iterations/sec2.8 it/s
Seconds per image8.93 sec (25 steps)
Images per minute6.72
Resolution512×512
SamplerEuler a / DPM++ 2M Karras
Performance ratingVery Good

Benchmark conditions: 25-step generation at 512×512, batch size 1, FP16 precision. Using A1111 WebUI or ComfyUI backend.

Memory Footprint on 6 GB

ComponentVRAM
Model weights3.2 GB
Sampling buffer~0.6 GB
Total RTX 3050 VRAM6 GB
Free headroom~2.8 GB

SD 1.5’s compact 3.2 GB footprint fits comfortably on 6 GB. You will not be running LoRA stacks or 768×768 generations without some VRAM tricks, but for standard 512×512 output the 3050 handles it cleanly. This makes it a strong candidate for dev environments or prototype servers where cost matters more than speed.

The Budget Equation

Cost MetricValue
Server cost£0.25/hr (£49/mo)
Cost per 1K images£0.62
Images per £11613

Sixty-two pence for a thousand images. At £49/mo, the RTX 3050 is hard to argue with if you are bootstrapping an image generation service or running SD 1.5 for internal tools. Compare with higher-end options on our benchmark page.

Best Fit for This Hardware

The RTX 3050 is not going to win any speed contests, but 6.72 images per minute at £49/mo is genuinely useful. Prototyping, internal creative tools, low-volume print-on-demand — all solid use cases. When you outgrow it, the RTX 4060 more than doubles throughput for £20/mo extra. See our GPU comparison for Stable Diffusion.

Quick deploy:

docker run --gpus all -p 7860:7860 ghcr.io/ai-dock/stable-diffusion-webui:latest --sd15

More resources: SD hosting guide, all benchmarks, Flux.1 hosting for next-gen comparison.

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