What Is Model Stacking?
Model stacking in generative AI refers to using multiple image and/or video generation models in sequence to achieve a desired visual outcome.
Not all generative models are created equally — some are stronger in certain areas (artistic style, prompt fidelity, texture, lighting, motion, etc.) than others. By stacking models together in a workflow, you can layer their strengths and mitigate weaknesses.
For example:
Midjourney is widely regarded for artistic style and composition quality.
Gemini (Nano Banana Pro / Gemini image models) excels in coherence and commercial-ready visuals.
Seedream produces ultra-realistic textures and upscaling consistency.
By stacking these tools — i.e., starting a concept in one and refining in another — you can blend creativity, fidelity, and finish.
Why Model Stacking Is Useful for Creatives
Each model has a specialty
Think of each model like a specialist artist: one excels in concept, another in texture, another in lighting, etc.Better final outputs with fewer constraints
You’re not tied to one tool’s strengths and limitations — you combine them.Faster iteration
Generate quickly in one model and refine details where needed.
How Simple Image Model Stacks Work
Workflow Example:
Concept Foundation: Generate the initial idea in a broad, creative model (e.g., GPT-4o or Midjourney) — good for establishing style, composition, and initial aesthetics.
Secondary Refinement: Take the output into a second model (like Nano Banana Pro) and use it to improve realism, character consistency, or editing specific parts of the scene.
Detail/Texture Pass: Feed the refined output to a model like Seedream if you need superior texture detail, material realism, or upscaling.
Final Pass (Optional): Use specialized tools (e.g., inpainting engines, photorealistic editors) to polish inconsistencies or add small elements.
Tip: To carry images between models, simply upload the image into the next model’s prompt interface and continue prompting. Nothing complex — just image upload + new instructions.
5 Popular Multi-Image Model Stacks Creatives Use
These are common chains used in the field:
Midjourney → Nano Banana Pro → Seedream
Artistic style + coherence + texture polish.GPT Text-to-Image (e.g., GPT-4o image gen) → Flux or Stable Diffusion Fusion → Midjourney Upscale
Concept visualization → refinement → artistic flair.ChatGPT / GPT-4o → DALL·E 3 → Nano Banana
Strong prompt interpretation → clean execution → detail/realism boost.Stable Diffusion XL (with ControlNet) → Midjourney → Adobe Firefly for business-ready edit
Fine control → aesthetics → professional layout.Open-Source Stack: Z-Image / Flux → Custom LoRAs → Midjourney (final stylistic pass)
Open-source base → personal style libraries → polished style output.
Video Prompt Stacking: How It Works
Just like image gen, not all video models are equal — some are stronger at motion realism, others at prompt adherence, others at style consistency.
You can stack for video the same way:
Frame or Reference Generation: Start with image models to create key frames or reference visuals.
Text-to-Video Base Pass: Use an AI video model (e.g., Veo 3.1, Sora, Runway Gen-4.5) to generate motion, using your key frames as input.
Refinement Animation Pass: Use slower, higher quality models or specialized tools to fix motion artefacts or regenerate shots with better continuity.
Video Model Characteristics
Veo 3.1: Great at image-to-video coherence, supporting multiple references.
OpenAI Sora: Known for expressive motion in stylized and social media-friendly formats.
Runway Gen-4.5: Strong fidelity and motion quality.
Use images from the previous step as inputs — just upload them and prompt naturally.
Top 10 Models for Image & Video Gen (and What They're Best At)
Image Models
Midjourney – Artistic and stylistic excellence.
Nano Banana Pro (Gemini) – Cohesive, commercial-ready outputs.
Seedream – Texture and photorealistic detail.
DALL·E 3 / GPT-4o – Strong prompt understanding and accurate execution.
Stable Diffusion XL – Deep prompt control and customization.
Flux – Customizable open-source creative base.
Adobe Firefly Image Model – Integration with professional workflows.
Recraft – Photorealism with strong rendering for commercial use.
Ideogram – Accurate text + creative visuals.
Open-Source Z-Image Family – Fast, efficient generation for developers.
Video Models
Google Veo (Veo 3.1 / Fast) – Image-to-video coherence.
OpenAI Sora – Stylized, expressive video generation.
Runway Gen-4.5 – High fidelity motion and quality.
Pika AI – Fast rendering for social and short-form clips.
Wan / Wan2.5 Series – Cinematic quality with rich detail.
Luma Ray2 Series – Lightweight and fast, good for quick edits.
Seedance Series – Realistic motion and affordability.
Hunyuan Video – Open-source video generation option.
Mochi Video Model – Artistic or stylized motion engines.
LetsEnhance Video Tools – Good for preserving identity/portrait continuity.
Final Tips for Stacking Workflows
Keep reference continuity: When uploading between models, use prompts like “preserve composition, enhance texture, refine lighting”.
Don’t over-complicate: Stacking isn’t about complex scripts — it’s about intention and using each model’s strength.
Iterate fast; refine slowly: Rough passes in fast models; polish in slower, higher-quality models.
