GLM-4.5: New SOTA Opensource KING! Powerful, Fast, & Cheap! (Fully Tested)


Summary

The video introduces two new large language models, GLM 4.5 and GLM 4.5 Air, discussing their parameters and context length, as well as evaluating their performance across various tasks. These models offer a hybrid switch between deep reasoning and tools, similar to Alibaba's approach, allowing flexibility in tasks like math and GPQA. Priced at $2.20 per 1 million input tokens, the models showcase strong coding capabilities by generating games, UI elements, to-do boards, and demonstrating spatial reasoning by identifying the liar in a theft scenario based on statements. Additionally, the models excel in web searches and content generation tasks, displaying adaptive searching and quick content generation abilities.


Introduction of GLM 4.5 and GLM 4.5 Air

Introduction of two powerful new large language models from the GLM family, GLM 4.5 and GLM 4.5 Air, with details on their total parameters and context length.

Evaluation and Comparison with Other Models

Discussion on the evaluation of GLM 4.5 and GLM 4.5 Air across 12 reasoning and coding tasks, ranking against models like Mind, Xi, Alibaba, Moonshot, and Deep Seek.

Hybrid Reasoning and Tool Switch

Features of the models including a hybrid switch between deep reasoning and tools, similar to Alibaba's approach, allowing flexibility in tasks like math, GPQA, and others.

Pricing and Access

Information on the pricing of the models at $2.20 per 1 million input tokens and 20 cents for 1 million output tokens, along with instructions on how to access and use the models.

Coding Capabilities

Exploration of the models' coding capabilities, including generating a Flappy Birds game, UI elements, to-do boards, and front-end development, showcasing the versatility and performance in coding tasks.

Spatial Reasoning Assessment

Testing the model's spatial reasoning capabilities through a scenario involving identifying the liar in a theft situation based on statements from individuals, demonstrating the model's logical reasoning abilities.

Web Search and Content Generation

Utilizing the model for web searches and content generation tasks, such as creating slide decks and retrieving current information, showcasing the model's adaptive searching and quick content generation.

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