Llama 4 Scout vs Maverick - Image Understanding Comparison
Compare image understanding capabilities of LLaMA 4 Scout and Maverick using a visual workflow that analyzes home decor scene descriptions.
The image depicts a living room with a couch, coffee table, and various decorative items. The home furnishing and home decor items in this image are:
- Couch: A light gray couch with wooden legs is positioned against the wall.
- Pillows: Two pillows are placed on the couch: one is a light beige color, while the other is yellow.
- Blanket: A light-colored blanket is draped over the right side of the couch.
- Coffee Table: A round, wooden coffee table with black metal legs sits in front of the couch.
- Books and Mug: Two white books stacked on top of each other, accompanied by a black mug, are placed on the coffee table.
- Rug: A light-colored rug covers the floor beneath the coffee table and couch.
- Plant: A potted plant is situated to the right of the couch.
- Painting: A large, colorful abstract painting hangs above the couch.
- Window: A window is located on the left side of the image, allowing natural light to enter the room.
These items contribute to the overall aesthetic and functionality of the living room.
The image depicts a modern living room with a neutral color palette and vibrant accents. The room is well-lit, with natural light pouring in through the windows on the left side of the image.
Here are the main points describing the home furnishing and home decor items in the image:
- Sofa
- Color: Light gray
- Style: Modern, minimalist design
- Features: Two throw pillows (one white, one yellow) and a blanket draped over the right armrest
- Coffee Table
- Material: Wooden top with black metal legs
- Shape: Round
- Items on top: Stack of two books, a black coffee mug
- Artwork
- Three large pieces of abstract art hanging on the walls
- Colors: Various bright colors (orange, pink, blue, yellow, purple)
- Frames: Black
- Plant
- Type: Tall, green plant with large leaves
- Location: In a white pot on the right side of the room
- Rug
- Color: Beige
- Material: Not specified
- Size: Large enough to fit under the sofa and coffee table
- Windows
- Number: Two
- Location: On the left side of the room
- Style: Modern, with white trim
In summary, the image showcases a stylish and inviting living room with a focus on clean lines, minimal ornamentation, and pops of color from the artwork and throw pillows. The overall aesthetic is calm and sophisticated, making it an ideal space for relaxation or socializing.
More Like This
Discover more flows that match your style.
AI Product Ad Video Maker
Use Minimax AI Director, Claude 3.7 & Eleven Labs TTS to create engaging short video ads with voiceovers.
AI Home Decor Designer
Visualize custom fabric designs on home decor items. Streamlines interior design process by overlaying patterns on curtains, cushions, and more.
AI Fabric Pattern Changer
Seamlessly apply new patterns to existing garment photos, preserving fabric texture and fit. Revolutionize product visualization for fashion e-commerce and design prototyping.
Comparing Image Understanding in LLaMA 4 Models
This workflow is designed to benchmark and compare the visual reasoning and image understanding capabilities of two different versions of LLaMA 4-based models: LLaMA 4 Scout and LLaMA 4 Maverick. It's particularly useful for evaluating how well these models can describe visual content-specifically in the context of home furnishing and interior decor.
How It Works
At the core of the workflow is a shared image input-a high-resolution photo of a modern living room featuring colorful wall art, a sofa, coffee table, decorative pillows, and other decor elements. This image is routed to two parallel nodes, each powered by a different LLaMA 4 variant (Scout and Maverick). Both nodes are prompted with the same instruction:
"Describe all the home furnishing and home decor items in this image."
Each model independently generates a textual output, which is then displayed for side-by-side comparison. This allows you to analyze differences in:
-
Object recognition accuracy (e.g. does the model see the artwork, plant, or rug?)
-
Level of detail (e.g. does it mention materials, positions, and textures?)
-
Descriptive richness (e.g. does it infer style or aesthetic choices?)
-
Hallucinations or omissions in the generated output
This is especially useful for teams building vision-language models or deploying multimodal applications where accurate scene interpretation is critical-such as in eCommerce, design tools, or real estate platforms.
How to Customize
You can easily adapt this workflow to your own use cases by:
-
Changing the input image to any other domain (e.g. fashion, food, outdoor scenes, product photography)
-
Editing the prompt to tailor the kind of information you want extracted (e.g. "Identify potential hazards in this image" or "Write a product description for this photo")
-
Swapping models by replacing the LLaMA 4 nodes with other multimodal models like GPT-4V, Gemini Pro, Claude 3, etc.
-
Adding evaluation logic to score or rank model responses based on criteria like completeness or alignment with ground truth labels
This modular setup makes it ideal for running rapid A/B tests across vision-language models.
Models Used in the Pixelflow
llama4-scout-instruct-basic
Unlock powerful multimodal AI with Llama 4 Scout basic, a 17 billion active parameters model offering leading text & image understanding.
llama4-maverick-instruct-basic
Llama 4 Maverick Instruct Basic is a 400B parameter powerhouse with 128 experts for unparalleled text and image understanding.
