Best Stable Diffusion Model for 12GB VRAM (12GB VRAM)
SDXL with the full toolkit — and the first card that really hosts SD 3.5 Medium
The best Stable Diffusion model for 12GB VRAM in 2026 is still SDXL — ~7GB in FP16, roughly 12–20 seconds per 1024px image on an RTX 3060 12GB, and 12GB finally gives it room for the full toolkit: ControlNet, a LoRA stack and higher resolutions at once. The 12GB-specific upgrade is SD 3.5 Medium (~9.9GB excluding text encoders) — the newest SD base model, which an 8GB card cannot hold comfortably. SD 1.5 stays the lightweight ControlNet workhorse.
Models that fit in 12GB VRAM
Tested reference: RTX 3060 12GB / RTX 4070. Figures are for a 1024px image.
| Model | Size | Build | VRAM used | Speed |
|---|---|---|---|---|
| WINNERSDXL 1.0 Best pick at 12GB — not because it changed, but because the card fits SDXL plus ControlNet plus LoRAs at once. ComfyUI / Forge / Automatic1111 | 3.5B | FP16 | ~7GB | ~12–20s / image (RTX 3060) |
| Juggernaut XL / Pony The SDXL finetunes — photoreal or characters out of the box, same footprint as base. Civitai checkpoint | 3.5B | FP16 | ~7GB | ~12–20s / image |
| SD 3.5 Medium Stability’s consumer SD 3.5 — better prompt adherence than SDXL and native generation up to ~1440px. 12GB is the first tier that holds it with all three text encoders loaded; on 8GB you would offload T5. ComfyUI (sd3.5_medium + text encoders) | 2.5B (MMDiT-X) | FP16 | ~9.9GB (excl. text encoders) | ≈SDXL-range (no solid 12GB benchmark) |
| SD 3.5 Large (FP8) It does fit — barely — with little headroom for anything else. Run it to compare quality, not as a daily driver; it is happier on 16GB. ComfyUI FP8 checkpoint | 8.1B | FP8 | ~11GB | appreciably slower than SDXL |
| SD 1.5 Still the lightweight workhorse with the largest ControlNet/LoRA library — and 12GB lets you stack extensions 8GB cannot. Automatic1111 / ComfyUI | 0.9B | FP16 | ~4GB | ~4–6s / image (512px) |
What won't fit in 12GB
- ✗SD 3.5 Large (FP16) (needs ~18GB) — The full-precision build needs a 24GB card; the FP8 squeeze above is the 12GB route.
- ✗Flux.1 dev (FP16) (needs ~24GB) — Not an SD model but the common question: full-precision Flux needs 24GB — on 12GB run Flux.1 dev FP8 (~11GB, see the Flux 12GB guide).
How to fit more in 12GB
- →Drop the --medvram flags you needed on 8GB — SDXL plus a ControlNet plus 2–3 LoRAs sits inside 12GB natively, and the flags only slow you down.
- →For SD 3.5 Medium, keep all three text encoders (CLIP-L, CLIP-G, T5-XXL) on the GPU — that is what 12GB buys. Offloading T5 to system RAM works but adds time to every prompt change.
- →1536px SDXL renders work without tiled VAE at 12GB; past that, tiling still saves you. Batches of 2–4 at 1024px are where a 12GB card quietly beats an 8GB one on throughput.
Quick start
git clone https://github.com/comfyanonymous/ComfyUIDrop an SDXL or SD 3.5 Medium model into models/checkpointsGo from "it runs" to actually building
All 519 chapters — running local models, RAG, agents, fine-tuning — plus the Python Lab and every course added later.
Frequently asked questions
Is 12GB VRAM good for Stable Diffusion?
It is the comfortable tier: SDXL at ~12–20s per 1024px image on an RTX 3060 12GB with ControlNet and LoRAs loaded, no memory flags, no tricks. Everything the 8GB guide does with caveats, 12GB does without them.
SDXL or SD 3.5 Medium on a 12GB card?
SDXL for most people — its finetune, LoRA and ControlNet ecosystem is still unmatched, and it is faster. SD 3.5 Medium (~9.9GB before text encoders) is worth running when prompt adherence matters more than style control, and 12GB is the smallest card that hosts it properly. Nothing stops you keeping both on disk.
Should I run SD or Flux with 12GB?
Both fit: SDXL (~7GB) and Flux.1 dev FP8 (~11GB) are each at home on 12GB. Flux wins on prompt adherence and text-in-image; SDXL wins on speed, finetunes and control tooling. Many 12GB users iterate in SDXL and render finals in Flux — see the Flux 12GB guide for that side.
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