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Stable Diffusion 3.5 is a three-model open-weight image-generation family introduced by Stability AI in October 2024. Large is positioned for quality and prompt adherence, Large Turbo for four-step speed, and Medium for consumer hardware. Stability AI framed the release as a renewed effort after saying Stable Diffusion 3 Medium had not met its standards or community expectations.
For painters, 3.5 offers options for local customization, conditional commercial use, later ControlNet extensions, and access through downloadable weights, APIs, and hosted platforms. Claims about quality, prompt adherence, and performance are vendor-reported rather than universal independent conclusions.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteStable Diffusion 3.5 is a three-model open-weight image-generation family introduced by Stability AI in October 2024. It was also a renewed effort after the company said the June 2024 Stable Diffusion 3 Medium release had not met its standards or community expectations.
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The family offers different trade-offs: Stable Diffusion 3.5 Large is positioned for quality and prompt adherence, Large Turbo for four-step speed, and Medium for consumer hardware. Stability AI promotes customization and downstream uses such as fine-tuning and LoRAs. The release combines open weights with a license whose commercial terms depend on the user’s circumstances.
What Stable Diffusion 3.5 actually includes
| Model | Best suited to | Specifications stated by Stability AI | Main trade-off |
|---|---|---|---|
| Stable Diffusion 3.5 Large | Quality-oriented workflows | 8.1 billion parameters; intended for approximately 1-megapixel output | More demanding than the smaller Medium model; no universal hardware requirement is stated here |
| Stable Diffusion 3.5 Large Turbo | Fast iteration and previews | Distilled Large model designed for four inference steps | Speed is the priority; do not assume it is best for every quality-sensitive job |
| Stable Diffusion 3.5 Medium | Consumer-hardware workflows | 2.5 billion parameters; stated generation range of 0.25–2 megapixels; Stability AI reported 9.9 GB of VRAM excluding text encoders to unlock full performance | The VRAM figure is not a universal minimum or complete system requirement |
These are launch-announcement specifications and characterizations from Stability AI, not independent benchmark results. Stability AI described Large as its quality- and prompt-oriented option, Turbo as considerably faster, and Medium as a smaller model intended for consumer hardware. The best choice depends on the workflow and hardware.
Why Stability AI released 3.5 after Stable Diffusion 3
Stable Diffusion 3 Medium arrived in June 2024 as the first open release in the Stable Diffusion 3 series. Stability AI later said it had not fully met the company’s standards or community expectations. The 3.5 announcement on October 22, 2024, therefore presented the release as a renewed effort, not simply a routine model update.
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Large and Large Turbo were introduced first; Medium was added to the announcement on October 29. Stability AI said it wanted to make the family more customizable and accessible across hardware tiers. Its stated aims included:
- Offer a larger model positioned for quality and prompt adherence.
- Offer a distilled model designed for four-step generation.
- Offer a smaller model intended for consumer hardware.
- Encourage downstream fine-tuning, LoRAs, optimizations, applications, and artwork workflows.
- Provide access through downloadable weights, an API, and hosted platforms.
Stability AI described improvements in prompt adherence, image quality, diversity, and stylistic range. Treat these as company claims: the launch materials do not establish a universal ranking or independent benchmark conclusion. Stability AI also noted a trade-off: different seeds can yield greater variation, and less-specific prompts can produce more uncertain outcomes or variable aesthetics.
Large, Large Turbo, and Medium in more detail
Stable Diffusion 3.5 Large
Large is the flagship base model. Stability AI describes it as an 8.1-billion-parameter model intended for professional use at approximately 1 megapixel. The company presents it as the quality- and prompt-oriented option, but that characterization is not a guarantee that every image or prompt will perform as intended.
For a painter, Large is a reasonable starting point when a prompt includes several interacting requirements, such as subject, composition, materials, lighting, environment, and typography. Compare outputs on your own prompts and workflow rather than relying on a single example or vendor claim.
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Stable Diffusion 3.5 Large Turbo
Large Turbo is a distilled version of Large designed to generate images in four inference steps. Stability AI presents it as considerably faster, making it a potential fit for composition searches, palette exploration, or interactive workflows. The four-step design does not make it universally preferable to Large for final-image work.
Stable Diffusion 3.5 Medium
Medium contains 2.5 billion parameters and is intended to run on consumer hardware. Stability AI gives a generation range of 0.25–2 megapixels and reports that 9.9 GB of VRAM, excluding text encoders, can unlock its full performance. That reported figure concerns Medium; it is not a complete system requirement or a promise that a particular computer will run every workflow comfortably.
Actual memory use depends on the inference software and setup. If you are planning a local image-generation system, a 12GB graphics card for local image generation may offer more headroom than treating the reported Medium figure as a hard target. Check compatibility with the software and model variant you plan to use.
What the architecture means for artists and developers
Stability AI describes Stable Diffusion 3.5 as part of its Multimodal Diffusion Transformer family. The launch announcement says Query-Key Normalization was used in transformer blocks to stabilize training and simplify fine-tuning and development. These are the company’s descriptions of the design and its aims.
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Prompt adherence, variety, and the quality trade-off
Stability AI presented 3.5 as an improvement in prompt adherence, quality, diversity, and style range. These are vendor claims, not proof that every prompt will be followed or that competing systems will produce worse results. Hands, lettering, spatial relationships, and small objects still warrant inspection.
The launch materials also note that greater variation across random seeds can preserve a broader range of outcomes, while an underspecified prompt may yield more uncertain results. Variation can help during exploration but frustrate workflows that need repeatability.
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A practical prompting sequence for painters is:
- State the subject and action. Identify what is being depicted and what is happening.
- Define composition. Add viewpoint, crop, scale, focal point, and negative space.
- Define visual language. Specify medium, surface, brushwork, palette, contrast, and lighting.
- Add constraints. Note elements that must be absent or subordinate.
- Iterate by changing one variable. Changing several things at once makes it harder to understand the result.
Stability AI claims improvements in typography, but text generation should still be checked character by character before treating an image as finished lettering.
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On November 26, 2024, Stability AI announced ControlNets for Stable Diffusion 3.5 Large: Blur, Canny, and Depth. These are follow-on capabilities, not features to treat as part of the original October launch.
- Canny uses edge maps to structure generation.
- Depth uses depth maps to guide composition.
- Blur was described for high-fidelity upscaling and tiled large images.
These options can help artists use a source image or structural guide rather than relying on a text prompt alone. Stability AI announced weights on Hugging Face, code on GitHub, and ComfyUI support. Its reported preference study of approximately 150 participants ranked its ControlNets first among similar models; this is a company-reported result from the comparison it tested, not a universal ranking.
How to choose the right 3.5 model
| Your priority | Starting point | Why |
|---|---|---|
| Quality-oriented base generation | Large | Stability AI positions it as the flagship 8.1-billion-parameter model for approximately 1-megapixel output. |
| Fast visual exploration | Large Turbo | It is distilled for four inference steps. |
| Local generation on consumer hardware | Medium | It is the smaller model; the reported 9.9-GB VRAM figure excludes text encoders and is not a universal requirement. |
| Edge- or depth-guided structure | Large with a relevant ControlNet | Blur, Canny, and Depth were announced for Large in November 2024. |
| Managed deployment | Check current API or hosted-service options | Availability and routing can change; verify the provider’s current model, region, terms, and pricing. |
How you can access Stable Diffusion 3.5
Local inference
The October 2024 launch announcement listed downloadable weights on Hugging Face and inference code on GitHub, alongside other access routes. Repository access and license terms may apply. Local inference gives you control over files and settings, but requires compatible hardware and a suitable software setup; “runs locally” does not mean it runs on every PC.
ComfyUI can provide a visible node-based workflow. A ComfyUI Stable Diffusion 3.5 workflow may be a practical starting point, but check that it matches the model variant and supporting files you install.
Hosted APIs and managed services
The launch announcement listed the Stability AI API and hosted access through Replicate, Fireworks AI, and DeepInfra, as well as ComfyUI. Availability can change. Stability AI’s API documentation records that selected older SD3 identifiers were routed to SD3.5 equivalents beginning April 17, 2025, at the same price at that time; do not assume that routing or pricing remains current.
Before building around Stable Diffusion 3.5 on Amazon Bedrock, verify current model availability, regions, account requirements, and pricing with the provider. Managed inference avoids maintaining a local inference stack but introduces provider-specific terms and costs.
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In June 2025, Stability AI and NVIDIA announced TensorRT and FP8 optimizations for SD 3.5 on supported NVIDIA RTX GPUs. Stability AI reported up to 2.3 times faster generation for Large, up to 1.7 times for Medium, and 40% lower memory requirements. These are company-reported figures tied to optimized models and supported hardware, not universal performance promises.
On August 12, 2025, Stability AI and NVIDIA announced an SD 3.5 NIM microservice initially supporting Large, with enterprise and data-center Ada and Blackwell GPUs described in the announcement. Treat Stable Diffusion 3.5 NIM as a dated enterprise deployment route, not evidence that every variant is supported through the same service.
What “open” means here
Stable Diffusion 3.5 is an open-weight model family, not an unrestricted release with no applicable terms. Stability AI’s October 2024 launch announcement summarized its Community License as free for noncommercial use and free commercial use for organizations with less than $1 million in annual revenue, with larger organizations directed to inquire about an Enterprise License.
However, Stability AI’s Core Models page, last updated May 20, 2026, lists SD 3.5 Medium, Large, and Large Turbo as available to Community and Enterprise users for commercial use under their applicable agreement. Review the actual current agreement and model scope for your use; do not assume the launch-post summary overrides it. If relevant, consult Stability AI API information, but do not infer legal coverage or pricing from API availability alone.
The launch announcement says users retain ownership of generated media. That statement is not a guarantee that every generated image is copyrightable or free of training-data, publicity-rights, trademark, contract, or jurisdiction-specific concerns.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the release means for a painting workflow
Stable Diffusion 3.5 can be used as a visual development instrument rather than an automatic replacement for artistic judgment. A practical workflow might look like this:
- Begin with a thumbnail or rough block-in. Use a sketch, simple 3D composition, or reference you are entitled to use.
- Choose the model by task. Try Turbo for rapid exploration, Medium for a smaller consumer-hardware option, or Large for quality-oriented work.
- Use a ControlNet when structure matters. Canny uses edge maps, Depth uses depth maps, and Blur was described for upscaling and tiled large images.
- Generate variations deliberately. Change one variable at a time, such as palette, lighting, brushwork, crop, or environment.
- Inspect typography and anatomy manually. Vendor-reported improvements do not eliminate the need for correction.
- Paint over, composite, or use the result as reference. Use the model to explore alternatives, then apply your own judgment.
For repeatable work, record the model variant, prompt, seed, resolution, inference settings, ControlNet input, and software version. Large, Turbo, and Medium are not interchangeable, and software or hardware changes can affect results.
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Limitations to keep in view
- Vendor claims are not independent benchmarks. Attribute comparative quality, prompt-adherence, preference, and performance claims to Stability AI or the relevant partner.
- VRAM figures are partial. Stability AI’s 9.9-GB figure concerns Medium and excludes text encoders.
- Variants differ. Do not assume Large, Turbo, and Medium behave identically.
- Variation is intentional. Different seeds can produce greater variation; vague prompts may be less predictable.
- Availability changes. Check current service, API routing, regional availability, and license terms before deployment.
- Optimization figures have a defined scope. The TensorRT/FP8 results apply to supported NVIDIA RTX hardware and optimized models, as described by Stability AI.
Bottom line
Stable Diffusion 3.5 was Stability AI’s renewed effort after it said Stable Diffusion 3 Medium had not met expectations. The family offers Large, four-step Large Turbo, and Medium, with later ControlNets and NVIDIA optimizations extending the original launch.
For painters, its value is the choice of model and workflow, not a blanket promise of superior images. Compare outputs for your task, check hardware and current service availability, and review the applicable license before commercial use.
FAQ
What is Stable Diffusion 3.5?
It is Stability AI’s open-weight image-generation family introduced in October 2024, with Large, Large Turbo, and Medium variants.
Which SD 3.5 model should I use: Large, Large Turbo, or Medium?
Stability AI positions Large for quality-oriented work, Large Turbo for four-step speed, and Medium for consumer hardware. These are vendor characterizations; compare them on your own workflow.
How much VRAM does Stable Diffusion 3.5 need?
Stability AI reported 9.9 GB excluding text encoders for Medium to unlock full performance. This is not a universal minimum or a complete system requirement, and it does not describe Large or every workflow.
Can I run Stable Diffusion 3.5 locally?
The launch announcement listed downloadable weights and inference code. Local use depends on compatible hardware, software, and the applicable repository terms.
Can I use Stable Diffusion 3.5 commercially?
Check the current applicable agreement. Stability AI’s 2026 Core Models page lists the three SD 3.5 variants as available for commercial use under Community and Enterprise agreements; the October 2024 launch announcement separately summarized a revenue threshold for its Community License.
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Is Stable Diffusion 3.5 completely open source and copyright-free?
It is an open-weight release subject to applicable license terms, not an unrestricted public-domain release. Its license does not settle every copyright, training-data, publicity-rights, trademark, or contract question.
Is Stable Diffusion 3.5 Large Turbo better than Large?
Turbo is designed for four-step generation and speed. Whether it is preferable depends on the task; it is not universally better than Large.
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