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Benchmarks / Diffusion /Entry / BF16

Diffusion · Entry · BF16

A 4B-class model at BF16 on 12 GB. The universal baseline: every supported NVIDIA GPU from an RTX 3060 12 GB upward runs this identically, so it is the one leaderboard that spans the whole hardware range.

Best Seconds / step
s/step
Ranked results
0
0 distinct systems
GPU models
0
Minimum VRAM
12 GB
~14 min run

Best result per GPU

Seconds / step · s/step
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GPUGPUsSamplesBest (s/step)Mean (s/step)

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What is pinned

Everything below is fixed by the profile and checked on every submission. A result whose runtime flags differ from these is published, but never ranked.

Model
Repository
stabilityai/stable-diffusion-xl-base-1.0
Revision
pending freeze
Precision
bf16
Parameters
4 B
Licence
CreativeML-Open-RAIL-M++
Runtime
Engine
diffusers 0.39.0
Harness
diffusion-adapter
torch_dtype
float16
enable_attention_slicing
false
enable_vae_slicing
false
enable_model_cpu_offload
false
torch_compile
false
Workloads
t2i_1024
width=1024 height=1024 steps=30 scheduler=DPMSolverMultistep guidance_scale=5
Ranking
Ranked on
Seconds / step (s/step, lower is better)
Gate
Error rate ≤ 0
Gate
CPU offload ≤ 0
Also shown
Images / min, Per image p50, Per image p95, Energy / image, Pipeline load
Design notes
  • Release candidate. The runtime and harness versions are pinned; the model revision is not frozen until the bake-off confirms fit on the tier's minimum-VRAM reference system, so this leaderboard is provisional.
  • Ranked on seconds per denoising step: it is resolution- and step-count-normalised, so it stays comparable if a future profile changes step count. Images per minute is derived from it and is the headline shown to readers.
  • Diffusion is compute-bound where the LLM profiles are bandwidth-bound. This is deliberate: it is the counterweight that stops the site being one memory-bandwidth chart in three costumes.
  • CPU offload is disabled and gated. A run that offloads is published but never ranked, because it measures the host as much as the GPU.