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GLM-4.5 (Full Test) – The Fastest & Cheapest Open-Source Rival to GPT-4!
Content Introduction
The video introduces Z.A.I.'s new GLM 4.5 series, showcasing its powerful capabilities for intelligent agent applications. The series includes GLM 4.5 and GLM 4.5 Air, both designed for agent-oriented tasks, with the former having 355 billion parameters and the latter being lightweight with 106 billion. The models are trained on 15 trillion tokens, enabling them to perform tasks such as code generation, deep reasoning, and agent workflows. Featuring hybrid thinking modes, they adapt based on task complexity for better performance. With extensive output capabilities, GLM 4.5 can generate documents and fully functional code quickly, demonstrating exceptional performance in coding challenges and multi-turn tasks. The video emphasizes the versatility of GLM 4.5 in creating various applications, from games to full-stack solutions, all powered by simple prompts. The narrator concludes by encouraging viewers to explore the capabilities of GLM 4.5 and to engage further with the content.Key Information
- Z.A.I. introduces the GLM 4.5 series, designed for intelligent agent applications.
- GLM 4.5 boasts 355 billion active parameters, while GLM 4.5 Air has 106 billion parameters.
- Both models were trained on 15 trillion tokens and fine-tuned for various tasks, including code generation and reasoning.
- The models support a massive context length of 128,000 tokens and can manage extensive input and output, handling up to 96,000 output tokens.
- GLM 4.5 features hybrid thinking modes, including non-thinking for instant responses and thinking mode for complex reasoning.
- The training results show that GLM 4.5 ranks number two globally, leveraging high parameter efficiency over larger models.
- Real-world applications demonstrate GLM 4.5's capability in multi-turn agent coding tasks and responsive code generation.
- Prompts used to generate business proposals and code are executed quickly and efficiently, producing professional-quality outputs.
- The platform facilitates easy integration for developers via SDKs, promoting accessibility for creating intelligent applications.
Timeline Analysis
Content Keywords
GLM 4.5
Z.A.I.'s GLM 4.5 series is a powerful AI model designed for intelligent agent applications, featuring 355 billion parameters for complex tasks and hybrid thinking modes to support various computational tasks.
GLM 4.5 Air
The lightweight variant of GLM 4.5, the Air version, has 106 billion total parameters and is ideal for users needing a more cost-effective and efficient AI solution.
AI Training Strategy
Both GLM models are pre-trained on a colossal 15 trillion tokens and fine-tuned on tasks such as code generation and deep reasoning.
Hybrid Thinking Modes
GLM 4.5 supports dual thinking modes: a non-thinking mode for quick responses and a thinking mode for complex reasoning, facilitating a wide range of applications.
Token Management
GLM 4.5 can handle up to 96,000 output tokens and has a context length of 128,000 tokens, allowing for extensive input-output capabilities.
Real-World Performance
In industry-standard tests, GLM 4.5 ranks highly, delivering reliable results especially in multi-turn coding tasks and providing context-aware responses.
Development Tools
Users can easily implement GLM 4.5 in applications using the ZI SDK and Python, effectively making it a foundational tool for developing intelligent agents.
Application Examples
GLM 4.5 can generate business proposals, analyze code, build gaming applications, and create dynamic web components, showcasing its versatility and efficiency.
Call to Action
Viewers are encouraged to try GLM 4.5 for free to explore its powerful capabilities in building smarter and more humanlike AI applications.
Related questions&answers
What is Z.A.I.?
What are the key features of the GLM 4.5 series?
What is the difference between GLM 4.5 and GLM 4.5 Air?
How are GLM 4.5 models trained?
What is the maximum context length supported by GLM 4.5?
What are the supported input and output modalities of GLM 4.5?
How many output tokens can GLM 4.5 handle?
What applications can GLM 4.5 facilitate?
How does GLM 4.5 rank globally?
What are some practical use cases for GLM 4.5?
How easy is it to integrate GLM 4.5 into applications?
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