ShengShu Technology's text-to-image and reference-to-image model with support for character consistency and multi-reference image processing
Details
vidu-q2
Providers & Pricing (1)
Vidu Q2 is available exclusively through fal.ai, starting at $0.1/image.
fal/vidu-q2
Vidu Q2 API OpenAI-compatible
Vidu Q2 is available via the Lumenfall OpenAI-compatible API for generating high-consistency images and performing multi-reference image editing.
https://api.lumenfall.ai/openai/v1
vidu-q2
Text to Image Generate
Create images from text descriptions
curl -X POST \ https://api.lumenfall.ai/openai/v1/images/generations \ -H "Authorization: Bearer $LUMENFALL_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "vidu-q2", "prompt": "A serene mountain landscape at sunset", "size": "1024x1024" }'# Response:# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://api.lumenfall.ai/openai/v1'});const response = await client.images.generate({ model: 'vidu-q2', prompt: 'A serene mountain landscape at sunset', 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.generate( model="vidu-q2", prompt="A serene mountain landscape at sunset", size="1024x1024")# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }print(response.data[0].url)Image Editing Edit
Transform existing images with text instructions
curl -X POST \ https://api.lumenfall.ai/openai/v1/images/edits \ -H "Authorization: Bearer $LUMENFALL_API_KEY" \ -F "model=vidu-q2" \ -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: 'vidu-q2', 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="vidu-q2", 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)Gallery
View all 2 imagesVidu Q2 FAQ
Vidu Q2 starts at $0.1 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.
You can use Vidu Q2 through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "vidu-q2". Code examples are available in Python, JavaScript, and cURL.
Vidu Q2 is available through fal.ai on Lumenfall. Lumenfall automatically routes requests to the best available provider.
Overview
Vidu Q2 is a specialized image generation model developed by ShengShu Technology that prioritizes structural control and character consistency. Unlike standard text-to-image models that often struggle to maintain identity across multiple generations, Vidu Q2 is designed to process multiple reference images to anchor the visual features of a subject. This makes it a functional tool for creators who need to place the same character or object into varying environments and poses without losing visual fidelity.
Strengths
- Character Consistency: The model excels at preserving the identity, facial features, and attire of a subject when provided with reference images, reducing the “hallucination” of new traits between frames or shots.
- Multi-Reference Processing: It can ingest and synthesize information from more than one reference image simultaneously, allowing for better 360-degree understanding of a subject’s geometry and textures.
- Structural Adherence: Vidu Q2 demonstrates high accuracy in following compositional instructions, ensuring that the spatial relationship between the subject and the background remains coherent.
- Prompt Alignment: It maintains a strong correlation between complex text prompts and the resulting visual elements, even when constrained by specific image references.
Limitations
- Style Rigidity: Because the model focuses heavily on consistency, it may sometimes inherit unwanted lighting or stylistic artifacts from the reference images, making it difficult to completely pivot to a drastically different art style without significant prompting effort.
- Attribute Bleeding: When using multiple reference images with conflicting details (e.g., a character wearing different hats in two photos), the model may intermittently blend these features in unexpected ways.
- Lower Creative Variance: Users seeking “happy accidents” or high stylistic diversity may find the model’s output overly constrained compared to more generalized diffusion models like Stable Diffusion XL or Flux.
Technical Background
Vidu Q2 is part of the Vidu family of generative models, utilizing a transformer-based architecture optimized for multimodal inputs. The model’s key technical differentiator is its specialized attention mechanism that gives weighted priority to visual tokens extracted from reference images. This training approach allows the model to treat reference images as “hard constraints” rather than mere stylistic suggestions, ensuring the generated output remains grounded in the provided visual data.
Best For
Vidu Q2 is best suited for storyboarding, character design, and brand-consistent marketing campaigns where maintaining a singular “hero” subject is critical. It is an effective choice for game developers and concept artists who need to visualize a character in multiple scenarios or lighting conditions.
Vidu Q2 is available to explore through the Lumenfall playground and can be integrated into production workflows via the Lumenfall unified API, providing a consistent interface for high-fidelity character generation.
Try Vidu Q2 in Playground
Generate images with custom prompts — no API key needed.