AI Technology Evaluation (AITE)
NIST's sequestered testbed for blind-data evaluation of AI models, launching with vision-language tasks in quantum science, genomics, and public safety.
Overview
NIST's Technology Test and Evaluation Division announced the Artificial Intelligence Technology Evaluation (AITE) program in July 2026, providing researchers a sequestered testbed environment to evaluate AI model performance on blind data across diverse datasets, modalities, and domains, mitigating train/test contamination risk. NIST provides common data, metrics, and scoring so developers can compare model performance under a consistent, objective standard. AITE launches with three initial tasks: large vision-language model (VLM) image analysis in quantum science, genomics, and public safety, with plans to add more tasks under themes such as Quantum, Video, and NLP over time.
This is a sourced directory entry. Features and capabilities are reported in the linked sources; this entry does not document independent Aymorphic testing.
Key features
- Sequestered testbed environment for blind-data model evaluation
- Mitigates train/test data contamination risk
- Common data, metrics, and scoring across submissions
- Launch tasks: VLM image analysis for quantum science, genomics, and public safety
- Planned expansion into additional themes (Quantum, Video, NLP)
Use cases
- Objective, contamination-resistant benchmarking of vision-language models
- Comparing model performance on specialized scientific/public-safety imagery tasks
- Community AI evaluation research
Pricing
Not applicable (free government-run evaluation program for volunteer participants).
Pricing reflects the source record and may change. Confirm current terms with the provider.
Dates and sources
- Released
- 1 Jul 2026
- Record updated
- 23 Sept 2026
- Record last checked
- 23 Sept 2026