About MiniMax-M2.5 MiniMax-M2.5 is a state-of-the-art open-weights large language model released in February 2026. Built on a 230B-parameter Mixture of Experts (MoE) architecture with approximately 10 billion active parameters per forward pass, it features Lightning Attention and supports a context window of up to 205,000 tokens. The model uses extended chain-of-thought reasoning to work through […]

GLM-5 is the latest open-weights reasoning model released by Z AI (Zhipu AI) in February 2026, characterized by high “thinking token” usage. It is a Mixture of Experts (MoE) model with 744B total parameters and 40B active parameters, scaling up from GLM-4.5’s 355B parameters. The model was pre-trained on 28.5T tokens and features a 200K+ […]

Modern large language models (LLMs) are incredibly powerful at understanding and generating text, but until recently they were largely static: they could only respond based on patterns in their training data. Function calling changes that. It lets language models interact with external logic — your own code, APIs, utilities, or business systems — while still […]

When large language models move from demos into real systems, expectations change. The goal is no longer to produce clever text, but to deliver predictable latency, responsive behavior, and reliable infrastructure characteristics. In chat-based systems, especially, how fast a response starts often matters more than how fast it finishes. This is where token streaming becomes […]