Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Anthroly serves as a specialized data laboratory and provider of expert data tailored for pioneering AI laboratories and modeling teams. The company acquires operational data from American enterprises—including workplace communications, emails, support inquiries, customer relationship management histories, phone calls, software code, engineering documentation, and various other records—and processes this information into de-identified datasets, reinforcement learning frameworks, agent pathways, supervised fine-tuning materials, and assessment tools. Additionally, Anthroly engages in the recruitment and evaluation of professionals such as engineers, scientists, medical experts, and specialists in Indic languages to develop expert-crafted tasks, benchmarks, model outputs, and evaluation metrics. Their projects often encompass bespoke sourcing, expert analysis, grading rubrics, automated assessment tools, and comprehensive quality evaluations. Anthroly emphasizes that its model involves licensing data with identifiers removed prior to transfer, ensuring that data usage remains within the limits set by contractual agreements. The initiation of expert-data projects can commence with a pilot phase lasting one to two weeks, while the pricing for licensing and project scopes is customized to meet individual client needs. This tailored approach allows for flexibility and precision, making it easier for clients to access the expertise they require.
Description
GLM-5 is a next-generation open-source foundation model from Z.ai designed to push the boundaries of agentic engineering and complex task execution. Compared to earlier versions, it significantly expands parameter count and training data, while introducing DeepSeek Sparse Attention to optimize inference efficiency. The model leverages a novel asynchronous reinforcement learning framework called slime, which enhances training throughput and enables more effective post-training alignment. GLM-5 delivers leading performance among open-source models in reasoning, coding, and general agent benchmarks, with strong results on SWE-bench, BrowseComp, and Vending Bench 2. Its ability to manage long-horizon simulations highlights advanced planning, resource allocation, and operational decision-making skills. Beyond benchmark performance, GLM-5 supports real-world productivity by generating fully formatted documents such as .docx, .pdf, and .xlsx files. It integrates with coding agents like Claude Code and OpenClaw, enabling cross-application automation and collaborative agent workflows. Developers can access GLM-5 via Z.ai’s API, deploy it locally with frameworks like vLLM or SGLang, or use it through an interactive GUI environment. The model is released under the MIT License, encouraging broad experimentation and adoption. Overall, GLM-5 represents a major step toward practical, work-oriented AI systems that move beyond chat into full task execution.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
APIFree
No
Cheaper Inference
No
Cherry Studio
No
Claude Code
No
Claw Code
No
Cline
No
Dessix
No
GLM Coding Plan
No
GLM-5-Turbo
No
Kilo Code
No
Integrations
APIFree
Yes
Cheaper Inference
Yes
Cherry Studio
Yes
Claude Code
Yes
Claw Code
Yes
Cline
Yes
Dessix
Yes
GLM Coding Plan
Yes
GLM-5-Turbo
Yes
Kilo Code
Yes
Pricing Details
U.S. data suppliers pay no listing fee or commission. Licensed records are priced individually after a de-identified sample review. Expert-data work can begin with a free or low-cost 1–2 week pilot.
Free Trial
No
Free Version
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Anthroly
Website
www.anthroly.com
Vendor Details
Company Name
Z.ai
Founded
2023
Country
China
Website
z.ai/