Average Ratings 0 Ratings
Average Ratings 0 Ratings
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.
Description
NVIDIA Alpamayo 2 Super stands as a pioneering open model tailored for robotaxis and autonomous vehicles, designed to navigate rare and intricate driving scenarios while generating decisions that developers can analyze, verify, and rely upon. Utilizing the foundations of NVIDIA Cosmos 3 Super Reasoner and enhanced through reinforcement learning, it merges commercial accessibility with the ability to handle multiple tasks related to autonomous driving. The model comprehensively analyzes full-surround camera input, integrating perspectives from the front, sides, and rear to adeptly manage lane changes, merges, unprotected turns, and complex intersections. In addressing each driving scenario, it can produce a planned trajectory for the vehicle, a chain-of-causation that elucidates the decision-making process, a meta-action such as yielding or stopping, and reasoning auto-labels for both training and validation purposes, along with visual question-answering outputs anchored in specific image regions. These interconnected outputs facilitate the correlation between the model's observations and the actions it undertakes, thereby enhancing transparency in autonomous decision-making. Additionally, this functionality supports developers in refining and optimizing the model's performance in real-world applications.
API Access
Has API
Yes
API Access
Has API
No
Integrations
APIFree
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
Ollama
Yes
Integrations
APIFree
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
Ollama
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
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
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Z.ai
Founded
2023
Country
China
Website
z.ai/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
nvidia.com