stable-diffusion-v1-4: Self-Hosting & Deployment Guide
stable-diffusion-v1-4 is an open-weight text-to-image model.
What is stable-diffusion-v1-4?
stable-diffusion-v1-4 is an open-weight text-to-image model, published by CompVis with open weights at CompVis/stable-diffusion-v1-4. LLM API does not route this model today, so there is no endpoint or code sample for it here. What this page does give you is the self-hosting picture: published weight sizes, the VRAM each quantisation needs and the commands to serve it yourself. Every figure is read from the public repository and refreshed weekly. At import it had 659,179 downloads on Hugging Face in the previous 30 days, under the creativeml-openrail-m licence.
How to run stable-diffusion-v1-4 yourself
Open weights (creativeml-openrail-m), 860M parameters. Below: how much memory the weights need at each quantization, which hardware fits them, and the commands to serve it.
stable-diffusion-v1-4 VRAM requirements
| Precision / quantization | Weights | Figure | Source |
|---|---|---|---|
| BF16 (full precision) | 1.7 GB | Estimate | 860M params × 2 bytes |
File size = actual download size on Hugging Face. Estimate = parameter count × bytes per weight. Weights only — the KV cache for long contexts needs extra memory; the fit tables below add 15% headroom as a rule of thumb.
GPU requirements: deploy stable-diffusion-v1-4 on your hardware
| Hardware | BF16 (full precision) |
|---|---|
| NVIDIA H200141 GB | 1× |
| NVIDIA H10080 GB | 1× |
| NVIDIA A100 80GB80 GB | 1× |
| NVIDIA L40S48 GB | 1× |
GPUs needed per variant.
| Hardware | BF16 (full precision) |
|---|---|
| AWS p5.48xlarge8× H100 · 640 GB | Fits |
| AWS p4de.24xlarge8× A100 80GB · 640 GB | Fits |
| AWS g6e.12xlarge4× L40S · 192 GB | Fits |
| Google Cloud a3-highgpu-8g8× H100 · 640 GB | Fits |
| Azure ND H100 v58× H100 · 640 GB | Fits |
Whole-instance GPU memory; public instance specs.
Not on LLM.API yet
We do not route this model through our API at the moment. Browse the models you can call today — most workloads have a close match already live.
Not available on LLM API yet
We do not route this model through our API at the moment, so there is no endpoint or code snippet for it yet. Browse the models you can call today — most workloads have a close match already live.
Browse available modelsWhen to Use — When NOT to Use
Use it if...
- You need images generated from a text prompt, or edited from a reference image (stable-diffusion-v1-4)
- You want image generation on the same LLM API key as your text models, with no extra vendor SDK
- Your pipeline can take the result as a URL or base64 payload rather than a streamed response
- You want per-image pricing you can read off the catalogue before you commit
Avoid if...
- You need a chat, coding or reasoning model — this model returns images, not text
- You need token-by-token streaming: image calls return once the picture is finished
- You need video, speech or embeddings; those are separate models in the catalogue
- Your licensing review has not cleared generated imagery for commercial use
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