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Alibaba Cloud

Frontier AI Lab
alibabacloud.com ↗

Also known as: Alibaba, Aliyun, 阿里云

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Grades from external scorecards. We mirror published grades only; per-source methodology lives at the link in each panel header. See the scorecards directory for cross-org comparison.

Foundation Model Transparency Index

by Stanford CRFMPublished 2025-12-01Source ↗
Overall:26
Agent Protocols
100
AI bug bounty
0
Amount of usage
0
AUP enforcement frequency
0
AUP enforcement process
100
Basic model properties
100
Benchmarked inference
0
Benefits Assessment
0
Capabilities evaluation
100
Capabilities taxonomy
100
Carbon emissions for final training run
0
Change log
100
Classification of usage data
0
Code access
0
Compute hardware for final training run
0
Compute provider
100
Compute usage for final training run
0
Compute usage including R&D
0
Consumer/enterprise usage
0
Crawling
0
Data acquisition methods
0
Data domain composition
0
Data laborer practices
0
Data language composition
0
Data processing methods
0
Data processing purpose
0
Data processing techniques
0
Data replicability
0
Data retention and deletion policy
0
Data size
100
Deeper model properties
100
Detection of machine-generated content
0
Development duration for final training run
0
Distribution channels with usage data
0
Documentation for responsible use
0
Downstream
22.2
Acceptable use policy
60
Accountability
33.3
Downstream mitigations
40
Impact
0
Model Behavior Policy
50
Post-deployment monitoring
0
Usage data
0
Energy usage for final training run
0
Enterprise mitigations
100
Enterprise users
0
External data access
0
External developer mitigations
100
External products and services
0
External reproducibility of capabilities evaluation
0
External reproducibility of mitigations evaluation
0
External reproducibility of risks evaluation
0
External risk evaluation
0
Feedback mechanisms
0
Foundation model roadmap
100
Geographic statistics
0
Government commitments
100
Government use
0
Instructions for data generation
0
Intermediate tokens
100
Internal compute allocation
0
Internal product and service mitigations
0
Internal products and services
0
Licensed data compensation
0
Licensed data sources
0
Misuse incident reporting protocol
0
Mitigations efficacy
0
Mitigations taxonomy
0
Mitigations taxonomy mapped to risk taxonomy
0
Model
40
Capabilities
50
Model cost
0
Model dependencies
100
Model access
50
Model information
75
Model Mitigations
0
Model objectives
100
Release
62.5
Model response characteristics
100
Risks
0
Model stages
100
Model theft prevention measures
0
New human-generated data sources
0
Notice of usage data used in training
0
Open weights
100
Organization chart
0
Oversight mechanism
0
Permitted and prohibited users
100
Permitted, restricted, and prohibited model behaviors
0
Permitted, restricted, and prohibited uses
100
Post-deployment coordination with government
0
Pre-deployment risk evaluation
0
Public datasets
0
Quantization
0
Regional policy variations
0
Release stages
0
Researcher credits
0
Responsible disclosure policy
0
Risks evaluation
0
Risks taxonomy
0
Risk thresholds
0
Safe harbor
0
Security incident reporting protocol
0
Specialized access
0
Synthetic data purpose
100
Synthetic data sources
100
System prompt
0
Terms of use
100
Top distribution channels
100
Train-test overlap
0
Upstream
17.6
Compute
11.1
Data Acquisition
16.7
Data Processing
0
Data Properties
20
Methods
66.7
Other resources
0
Usage data used in training
0
Users of internal products and services
0
Versioning protocol
100
Water usage for final training run
0
Whistleblower protection
0