Inference Model
Reasoning Big Model: Reasoning Big Model refers to a model that can enhance reasoning, logical analysis and decision-making capabilities based on the traditional big language model. They usually have additional techniques, such as reinforcement learning, neural symbolic reasoning, meta-learning, etc., to enhance their reasoning and problem-solving capabilities.
• For example: DeepSeek-R1, GPT-o3 perform outstandingly in logical reasoning, mathematical reasoning, and real-time problem solving.
Non-inference large models: Suitable for most tasks, non-inference large models generally focus on language generation, context understanding and natural language processing, but not on Such models usually learn language rules and generate appropriate content through training on large amounts of text data, but lack Reasoning and decision-making capabilities as complex as inference models.
• For example: GPT-3, GPT-4 (OpenAI), BERT (Google), mainly used for language generation, language understanding, text classification, translation And other tasks.
