AI That Works Out-of-the-Box
ZERO: A Fast, Lightweight, and Flexible
Vision Foundation Model

ZERO is a ready-to-use vision foundation model built for industrial use.
It doesn’t just see what it was trained on—ZERO sees, searches, and understands exactly what you need.

ZERO 2.2 update

  • Higher detection accuracy with text prompts — fewer missed detections

  • Better understanding of Korean and descriptive prompts — like “orange jacket”

  • More distinct confidence scores — easier threshold tuning

ZERO

ZERO: The World's First VFM Built for Industry
ZERO Achieved First Place at CVPR 2026
Few-Shot Object Detection Challenge

Vision AI expertise built on real-world industrial data — proven with first place in the few-shot object detection challenge at CVPR 2026, the world’s largest computer vision conference.

53.9mAP

2nd-place score: 51.6 · Organizer baseline: 33.3

5

First place in 5 of 7 evaluation categories

1st

From 4th in 2025 to 1st in one year

Game-Changer in Vision AI Adoption: ZERO

Traditional Vision AI Adoption Journey

comparison_steps

1Define Problems

2Collect Data

3Label Data

4Train a Model

5Deploy

vs

ZERO, Ready to Go from Day 1

zero_steps

1Define Problems

2Deploy

ZERO

ZERO is a ready-to-use vision foundation model built for industrial use.
It doesn’t just see what it was trained on—ZERO sees, searches, and understands exactly what you need.

Contact us
ZEROConventional AIConventional SI
Instant adaptation to new requirements

Only recognizes what was pre-trained

2-6 months for update

Flexible business expansion

Additional development and costs required

Sustainable and efficient management

Increased overhead from siloed solutions

Maintenance costs incurred

ZERO Instantly Understands Whatever It Sees

Text Prompt

Accurately find the objects you describe in natural language.

Image Prompt

Detect objects intuitively — upload an image or specify with boxes and points.

What Sets ZERO Apart

No Pre-Training, Ready Out-of-the-Box

No Pre-Training, Ready Out-of-the-Box

Skip complex data collection and training. Just prompt and deploy—ZERO is ready for production from the start.

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Real-Time Inference with Unmatched Performance

Real-Time Inference with Unmatched Performance

Real-time inference at 0.329 TFLOPs (640×640) with the lightweight model. Top-tier detection accuracy among publicly available models on Superb AI’s industrial benchmark.

See the model lineup
Intuitive Input Methods

Intuitive Input Methods

Use natural language and visual prompts (boxes/points) together for even more precise and intuitive object targeting.

Natural Language Prompts

Natural Language Prompts

Find any target object with plain language like “a red chair next to the window”—no pre-defined classes needed.

Continuous Performance Improvement

Continuous Performance Improvement

Improve performance across new domains and scenarios with an automated data pipeline.

Flexible Deployment

Flexible Deployment

Deploy anywhere—cloud or on-premise. Optimized for a wide range of hardware environments including GPU, NPU, and edge devices.

Effortless Integration

Effortless Integration

Easy integration through a usage-based API. Deploy directly to a SageMaker endpoint through AWS Marketplace.

Fully Integrated Solution

Fully Integrated Solution

ZERO is built into Superb AI Video Analytics, so you can deploy in real-world production environments with no additional development.

Go to Superb AI Video Analytics

Three Model Sizes for Different Use Cases —
from Maximum Accuracy to Real-Time Inference

From accuracy-critical inspection to real-time processing on edge devices. Whichever model size you choose, text and visual prompting work the same way.

ModelDeploy parametersActive parameters at inferenceRecommended for
ZERO-Tiny440M65MEdge · real-time processing
ZERO-Base500M125MGeneral purpose
ZERO-Large610M235MPeak accuracy

ZERO-Tiny runs real-time inference at 0.329 TFLOPs on 640×640 input, keeping most of the larger models’ detection performance while cutting operating costs in production.

2x detection accuracy, even with the model optimized for real-time inference

SPBEval Text-G / Visual-G AP · at 640×640

ModelActive parametersComputeText APVisual AP
ZERO-Tiny65.0M0.329 TFLOPs29.723.7
YOLOE-26x69.9M0.197 TFLOPs14.215.4

More than double the detection accuracy of similarly sized real-time detection models. Prompt caching keeps inference running in real time.

Experience ZERO’s Unmatched Performance

Measured on SPBEval, our industrial-domain benchmark — see the latest version’s benchmark performance and the gains delivered with each release.

ZERO 2.2 vs Open models

SPBEval Text AP · ZERO 2.2 (Large)

  • ZERO 2.2
    31.3
  • LLMDet
    20.6
  • Grounding DINO
    17.9
  • Qwen3-VL
    16.2
  • YOLOe
    13.8
  • OWLv2
    12.9
  • DINO-X
    12.8

SPBEval — Superb AI’s in-house industrial-domain benchmark · Visual AP charts follow the same format (ZERO 2.2 Visual-G 26.2 / Visual-I 56.3)

Improving with every version

SPBEval Text AP · trend by version

Have a Question?
Browse our FAQs below.

What are ZERO’s key performance advantages?

Can I deploy ZERO through AWS?

What’s the biggest difference between ZERO and conventional AI?

Do I need AI expertise or manual labeling to use ZERO?

What types of objects or situations can ZERO detect? Can it recognize new targets it hasn’t been trained on?

How long does it take to implement ZERO in real-world applications, and is it compatible with our existing video systems?