--- title: "stable-diffusion vs x-stable-diffusion" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/compvis-stable-diffusion-vs-stochasticai-x-stable-diffusion" tools: ["compvis-stable-diffusion", "stochasticai-x-stable-diffusion"] --- # stable-diffusion vs x-stable-diffusion *GraphCanon updated Jul 15, 2026* ## Verdict Pick stable-diffusion if stable-diffusion is a state-of-the-art latent text-to-image diffusion model underpinning image generation from textual inputs; pick x-stable-diffusion if x-stable-diffusion offers real-time inference for the Stable Diffusion model with a latency of 0.88s, leveraging AITemplate, nvFuser, TensorRT, and FlashAttention. [stable-diffusion](https://ommer-lab.com/research/latent-diffusion-models/) reports 73k GitHub stars, 11k forks, and 617 open issues, last pushed Jun 18, 2024. [x-stable-diffusion](https://stochastic.ai) has 557 stars, 34 forks, and 22 open issues, last pushed Dec 4, 2023. Figures are from public GitHub metadata via [stable-diffusion's repository](https://github.com/CompVis/stable-diffusion) and [x-stable-diffusion's repository](https://github.com/stochasticai/x-stable-diffusion). | | [stable-diffusion](/tools/compvis-stable-diffusion.md) | [x-stable-diffusion](/tools/stochasticai-x-stable-diffusion.md) | | --- | --- | --- | | Tagline | A latent text-to-image diffusion model | Real-time inference for Stable Diffusion - 0.88s latency | | Stars | 73,179 | 557 | | Forks | 10,584 | 34 | | Open issues | 617 | 22 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | Stable-diffusion is a state-of-the-art latent text-to-image diffusion model underpinning image generation from textual inputs. | x-stable-diffusion offers real-time inference for the Stable Diffusion model with a latency of 0.88s, leveraging AITemplate, nvFuser, TensorRT, and FlashAttention. | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | Computer Vision, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [stable-diffusion](/tools/compvis-stable-diffusion.md) | [x-stable-diffusion](/tools/stochasticai-x-stable-diffusion.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 753d | 950d | | Archived on GitHub | No | Yes | | Open issues (now) | 617 | 22 | | Full report | [trust report](/tools/compvis-stable-diffusion/trust.md) | [trust report](/tools/stochasticai-x-stable-diffusion/trust.md) | **Typed relationship:** stable-diffusion _(alternative)_ x-stable-diffusion x-Stable-Diffusion offers real-time inference for Stable Diffusion with reduced latency, providing an alternative approach to improving performance. ## Decision facts: stable-diffusion - **Adopt for:** Stable-diffusion is a state-of-the-art latent text-to-image diffusion model underpinning image generation from textual inputs. ## Decision facts: x-stable-diffusion - **Adopt for:** x-stable-diffusion offers real-time inference for the Stable Diffusion model with a latency of 0.88s, leveraging AITemplate, nvFuser, TensorRT, and FlashAttention. ## Choose when ### Choose stable-diffusion if… - License: stable-diffusion is Other, x-stable-diffusion is Apache-2.0. - x-Stable-Diffusion offers real-time inference for Stable Diffusion with reduced latency, providing an alternative approach to improving performance. - Tags unique to stable-diffusion: diffusion-model, latent space, text-to-image. - Also covers Computer Vision. - For generating images based on text prompts with high fidelity and artistic detail. ### Choose x-stable-diffusion if… - License: x-stable-diffusion is Apache-2.0, stable-diffusion is Other. - x-Stable-Diffusion offers real-time inference for Stable Diffusion with reduced latency, providing an alternative approach to improving performance. - Tags unique to x-stable-diffusion: aitemplate, automl, cuda, docker. - Also covers Inference & Serving. - When you require low-latency real-time inference performance at less than 1 second ## When NOT to use stable-diffusion - If the computational resources are limited, as it requires significant GPU power to train or fine-tune models. - In cases where real-time generation performance is critical, due to its computation-intensive process. ## When NOT to use x-stable-diffusion - For projects that do not require real-time performance or have higher latency tolerance - If the specific optimizations for Stable Diffusion are not aligned with your model needs ## Common questions ### What is the difference between stable-diffusion and x-stable-diffusion? stable-diffusion: A latent text-to-image diffusion model. x-stable-diffusion: Real-time inference for Stable Diffusion - 0.88s latency. See the comparison table for live GitHub stats and shared categories. ### When should I choose stable-diffusion over x-stable-diffusion? Choose stable-diffusion over x-stable-diffusion when License: stable-diffusion is Other, x-stable-diffusion is Apache-2.0; x-Stable-Diffusion offers real-time inference for Stable Diffusion with reduced latency, providing an alternative approach to improving performance; Tags unique to stable-diffusion: diffusion-model, latent space, text-to-image; Also covers Computer Vision; For generating images based on text prompts with high fidelity and artistic detail. ### When should I choose x-stable-diffusion over stable-diffusion? Choose x-stable-diffusion over stable-diffusion when License: x-stable-diffusion is Apache-2.0, stable-diffusion is Other; x-Stable-Diffusion offers real-time inference for Stable Diffusion with reduced latency, providing an alternative approach to improving performance; Tags unique to x-stable-diffusion: aitemplate, automl, cuda, docker; Also covers Inference & Serving; When you require low-latency real-time inference performance at less than 1 second. ### When should I avoid stable-diffusion? If the computational resources are limited, as it requires significant GPU power to train or fine-tune models. In cases where real-time generation performance is critical, due to its computation-intensive process. ### When should I avoid x-stable-diffusion? For projects that do not require real-time performance or have higher latency tolerance If the specific optimizations for Stable Diffusion are not aligned with your model needs ### Is stable-diffusion or x-stable-diffusion more popular on GitHub? stable-diffusion has more GitHub stars (73,179 vs 557). Stars measure visibility, not whether either tool fits your constraints. ### Are stable-diffusion and x-stable-diffusion open source? Yes - both are open-source projects on GitHub (stable-diffusion: Other, x-stable-diffusion: Apache-2.0). ### Where can I find alternatives to stable-diffusion or x-stable-diffusion? GraphCanon lists graph-backed alternatives at [stable-diffusion alternatives](/tools/compvis-stable-diffusion/alternatives) and [x-stable-diffusion alternatives](/tools/stochasticai-x-stable-diffusion/alternatives) ([stable-diffusion markdown twin](/tools/compvis-stable-diffusion/alternatives.md), [x-stable-diffusion markdown twin](/tools/stochasticai-x-stable-diffusion/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/compvis-stable-diffusion-vs-stochasticai-x-stable-diffusion.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, stable-diffusion or x-stable-diffusion? stable-diffusion: Dormant. x-stable-diffusion: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for stable-diffusion and x-stable-diffusion? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stable-diffusion trust report](/tools/compvis-stable-diffusion/trust); [x-stable-diffusion trust report](/tools/stochasticai-x-stable-diffusion/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=compvis-stable-diffusion`](/api/graphcanon/graph?tool=compvis-stable-diffusion) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_