Stable Diffusion 3.5 Large
AI Image Generation Model
Stability AI's 8.1-billion parameter Multimodal Diffusion Transformer (MMDiT) text-to-image model featuring improved image quality, typography, complex prompt understanding, and resource-efficiency
Details
stable-diffusion-3.5-large
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Full pricing detailsProviders & Pricing (1)
Stable Diffusion 3.5 Large is available exclusively through Replicate, starting at $0.065/image.
replicate/stable-diffusion-3.5-large
Stable Diffusion 3.5 Large API OpenAI-compatible
Integrate Stable Diffusion 3.5 Large into your application via Lumenfall’s OpenAI-compatible API to generate high-resolution images from text prompts. This unified endpoint provides programmatic access to the model's Multimodal Diffusion Transformer for scalable media generation.
https://api.lumenfall.ai/openai/v1
stable-diffusion-3.5-large
Code Examples
Image Edit
/v1/images/editscurl -X POST \ https://api.lumenfall.ai/openai/v1/images/edits \ -H "Authorization: Bearer $LUMENFALL_API_KEY" \ -F "model=stable-diffusion-3.5-large" \ -F "[email protected]" \ -F "prompt=Add a starry night sky to this image" \ -F "size=1024x1024"# Response:# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }import OpenAI from 'openai';import fs from 'fs';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://api.lumenfall.ai/openai/v1'});const response = await client.images.edit({ model: 'stable-diffusion-3.5-large', image: fs.createReadStream('source.png'), prompt: 'Add a starry night sky to this image', size: '1024x1024'});// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }console.log(response.data[0].url);from openai import OpenAIclient = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.lumenfall.ai/openai/v1")response = client.images.edit( model="stable-diffusion-3.5-large", image=open("source.png", "rb"), prompt="Add a starry night sky to this image", size="1024x1024")# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }print(response.data[0].url)Parameter Reference
Core Parameters
| Parameter | Type | Description | Modes |
|---|---|---|---|
prompt
|
string | Required. Text prompt for image generation |
T2I
Edit
|
negative_prompt
|
string | Negative prompt to guide generation away from undesired content |
T2I
Edit
|
seed
|
integer | Random seed for reproducibility |
T2I
Edit
|
Size & Layout
| Parameter | Type | Description | Modes |
|---|---|---|---|
size
|
string |
Image dimensions as WxH pixels (e.g. "1024x1024") or aspect ratio (e.g. "16:9")
WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.
|
T2I
Edit
|
aspect_ratio
|
string |
Aspect ratio of the output image (e.g. "16:9", "1:1")
Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.
|
T2I
Edit
|
resolution
|
string |
Output resolution tier (e.g. "1K", "4K")
1K
Controls scale independently of shape. Higher tiers produce larger images and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.
|
T2I
Edit
|
| Output |
size
|
aspect_ratio
+
resolution
|
|
|---|---|---|---|
| Flexible | |||
|
Custom
1–14142px per side
|
"WxH" |
— | Any pixel dimensions within model constraints |
1K 9 sizes
| Output |
size
|
aspect_ratio
+
resolution
|
|
|---|---|---|---|
| 916 × 1145 | "916x1145" |
or |
"4:5"
+
"1K"
|
| 1145 × 916 | "1145x916" |
or |
"5:4"
+
"1K"
|
| 1024 × 1024 | "1024x1024" |
or |
"1:1"
+
"1K"
|
| 836 × 1254 | "836x1254" |
or |
"2:3"
+
"1K"
|
| 1254 × 836 | "1254x836" |
or |
"3:2"
+
"1K"
|
| 768 × 1365 | "768x1365" |
or |
"9:16"
+
"1K"
|
| 1365 × 768 | "1365x768" |
or |
"16:9"
+
"1K"
|
| 670 × 1564 | "670x1564" |
or |
"9:21"
+
"1K"
|
| 1563 × 670 | "1563x670" |
or |
"21:9"
+
"1K"
|
How these parameters work
size
Exact pixel dimensions
"1920x1080"
aspect_ratio
Shape only, default scale
"16:9"
resolution
Scale tier, preserves shape
"1K"
Priority when combined
size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.
How matching works
7:1 on a model with
4:1 and 8:1,
you get 8:1.
0.5K 1K 2K 4K)
or megapixel tiers (0.25 1).
If the exact tier isn't available, you get the nearest one.
Media Inputs
| Parameter | Type | Description | Modes |
|---|---|---|---|
image
|
file |
Required.
Input image(s) to edit
Supports PNG, JPEG, WebP.
|
T2I
Edit
|
Output & Format
| Parameter | Type | Description | Modes |
|---|---|---|---|
response_format
|
string |
How to return the image
url
b64_json
Default:
"url" |
T2I
Edit
|
output_format
|
string |
Output image format
png
jpeg
gif
webp
avif
Gateway converts to requested format if provider doesn't support it natively.
|
T2I
Edit
|
output_compression
|
integer | Compression level for lossy formats (JPEG, WebP, AVIF) |
T2I
Edit
|
n
|
integer |
Number of images to generate
Default:
1Gateway generates multiple images in parallel even if provider only supports 1.
|
T2I
Edit
|
Additional Parameters
Provider-specific passthrough fields, available only when the request is routed to the listed provider.
| Parameter | Type | Description | Modes |
|---|---|---|---|
|
Universal
|
|||
cfg_scale
|
number | Classifier-free guidance scale — higher values stick more closely to the prompt |
T2I
Edit
|
strength
|
number | How much to transform the input image: 0 keeps it unchanged, 1 fully regenerates from the prompt |
T2I
Edit
|
Parameter Normalization
How we handle parameters across different providers
Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:
| Behavior | What happens | Example |
|---|---|---|
passthrough |
Sent as-is to the provider | style, quality |
renamed |
Same value, mapped to the field name the provider expects | prompt |
converted |
Transformed to the provider's native format | size |
emulated |
Works even if the provider has no concept of it | n, response_format |
Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.
Stable Diffusion 3.5 Large FAQ
How much does Stable Diffusion 3.5 Large cost?
Stable Diffusion 3.5 Large starts at $0.065 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.
How do I use Stable Diffusion 3.5 Large via API?
You can use Stable Diffusion 3.5 Large through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "stable-diffusion-3.5-large". Code examples are available in Python, JavaScript, and cURL.
Which providers offer Stable Diffusion 3.5 Large?
Stable Diffusion 3.5 Large is available through Replicate and fal.ai on Lumenfall. Lumenfall automatically routes requests to the best available provider.
What is the maximum resolution for Stable Diffusion 3.5 Large?
Stable Diffusion 3.5 Large supports images up to 1024x1024 resolution.
Overview
Stable Diffusion 3.5 Large is an 8.1-billion parameter text-to-image model developed by Stability AI. Built on the Multimodal Diffusion Transformer (MMDiT) architecture, it is designed to balance high-fidelity visual output with the ability to follow intricate, multi-part natural language instructions. This model represents a significant refinement in the Stable Diffusion lineage, focusing on improved prompt adherence and photorealism compared to its predecessors.
Strengths
- Complex Prompt Adherence: The model excels at interpreting long, descriptive prompts that include specific spatial relationships, multiple subjects, and detailed stylistic instructions.
- Typography and Text Rendering: It demonstrates a high degree of accuracy when generating legible text within images, minimizing the spelling errors common in earlier latent diffusion models.
- Subject Diversity: It is capable of generating a wide range of human skin tones, textures, and facial features without a strong inherent bias toward a single aesthetic style.
- Structural Composition: The MMDiT architecture allows the model to maintain better global consistency, ensuring that large-scale elements (like limbs or architectural features) are proportionally correct and logically placed.
Limitations
- Hardware Requirements: At 8.1 billion parameters, it requires significant VRAM for local inference, making it less suitable for consumer-grade hardware without quantization.
- Generation Speed: Due to its size and the complexity of the transformer-based backbone, it generally has higher latency per image compared to “Turbo” or “Lightning” versions of the SD3 family.
- Anatomical Edge Cases: While improved, the model can still struggle with extremely complex anatomical poses or highly overlapping human figures in crowded scenes.
Technical Background
The model utilizes a Multimodal Diffusion Transformer (MMDiT) architecture, which uses separate sets of weights for image and text representations but allows them to interact via a bidirectional flow of information. This approach enables the model to treat visual and textual data as equal contributors to the final output, improving the alignment between the user’s input and the generated pixels. The training process prioritized resource efficiency and stable convergence, allowing the 8.1B parameter model to outperform larger competitors in specific benchmark categories.
Best For
Stable Diffusion 3.5 Large is ideal for professional design workflows where precise control over composition and text is required, such as creating posters, book covers, or conceptual art from detailed briefs. It is a strong choice for users who need a versatile, general-purpose model that can handle both photorealistic and stylized requests without extensive fine-tuning.
This model is available for testing and integration through Lumenfall’s unified API and playground, allowing you to compare its output alongside other industry-standard image generation models.
Try Stable Diffusion 3.5 Large in Playground
Generate images with custom prompts — no API key needed.