Anthropic has released Claude 3.7 Sonnet and Claude Code. Claude 3.7 Sonnet, the world's first hybrid reasoning model, boasts a unique reasoning mode and exceptional performance; Claude Code is a powerful intelligent coding tool. Their release has garnered significant attention in the AI field, offering users more efficient and intelligent services and development experiences.

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Introduction to Claude 3.7 Sonnet

  • Hybrid Reasoning Mode: Claude 3.7 Sonnet is Anthropic's most intelligent model to date and the world's first hybrid reasoning model. It integrates standard thinking and extended thinking modes. In standard mode, it's an upgrade of Claude 3.5 Sonnet, providing quick responses; in extended thinking mode, the model performs self-reflection before providing answers, significantly improving performance in tasks such as mathematics, physics, instruction following, and coding.
  • Controllable Thinking Time: API users can control the model's thinking budget, instructing Claude to think for no more than N tokens (N has a maximum value of the 128K token output limit), balancing speed (and cost) with answer quality.
  • Performance Optimization Focus: Development prioritized real-world tasks reflecting how businesses actually use LLMs, with less optimization for math and computer science competition problems. Claude 3.7 Sonnet achieved excellent results in several benchmark tests, such as SWE-bench Verified (evaluating AI models' ability to solve real-world software problems) and TAU-bench (testing AI agents' ability to interact with users and tools in complex real-world tasks).
  • Enhanced Security: Claude 3.7 Sonnet makes finer distinctions between harmful and benign requests, reducing unnecessary rejections by 45% compared to its predecessor.

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Claude 3.7 Sonnet Key Features

  • Powerful Reasoning Capabilities: In extended thinking mode, it can perform step-by-step reasoning for complex problems. For example, when solving the Monty Hall problem (a game theory math problem), it demonstrates the detailed thought process, helping users understand the solution.
  • Exceptional Coding Abilities: It excels in coding and front-end web development, achieving high scores of 70.3% (using a custom framework) and 62.3% (standard framework) in the SWE-bench Verified benchmark test. This significantly surpasses models like OpenAI's o3-mini (high) and DeepSeek R1, enabling developers to efficiently complete programming tasks such as creating complex games, implementing physical simulations, and recreating web pages.
  • Good Multimodal Capabilities: It shows significant improvement in integrated text and image processing, possessing the potential to handle multimodal tasks and function effectively in complex scenarios involving images and text.
  • Precise Instruction Understanding and Execution: It demonstrates excellent instruction following, accurately understanding and executing user instructions. It achieved a high score of 93.2% in the IFEval test, efficiently completing various tasks instructed by users.
  • Broad Language Support and Understanding: It achieved an 86.1% score in the Multi-lingual Language Understanding Evaluation (MMMLU) test, indicating strong understanding and processing capabilities for multiple languages, catering to users of different linguistic backgrounds.
  • Intelligent Problem-Solving Capabilities: It excels at solving problems in mathematics, physics, and other subjects. For example, it achieves 96.2% accuracy in the MATH 500 test, providing effective problem-solving assistance for students and researchers.
  • Flexible Switching of Thinking Modes: Users can easily switch between standard and extended thinking modes based on their needs to handle problems of varying complexity. Standard mode is suitable for simple, quick answers, while extended thinking mode is for complex tasks.
  • Customizable Thinking Budget: API users can precisely set the number of tokens for the model's thinking process based on task requirements, flexibly controlling thinking time and cost, balancing answer quality and retrieval speed.

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Application Scenarios

  • Programming Development: Assists developers in writing code, debugging programs, and optimizing code structure. When developing games, applications, or websites, it can quickly generate code frameworks and solve problems in the code, improving development efficiency.
  • Academic Research: Assists researchers in conducting literature reviews, analyzing research problems, and designing experiments. It provides professional knowledge and logical analysis support when dealing with complex academic issues.
  • Content Creation: Provides inspiration for writers, editors, and other creative professionals, assisting in writing articles, stories, reports, and other content, improving the quality and efficiency of creation.
  • Intelligent Customer Service: Used in enterprise customer service systems to quickly and accurately answer customer questions, understand customer needs, and provide high-quality service experiences.
  • Data Analysis: Analyzes and interprets large amounts of data, helping businesses or researchers extract valuable information from data, enabling trend prediction and decision support.
  • Education: As an intelligent tutoring tool, it helps students solve problems in various subjects, provides learning methods and approaches, and assists teachers in teaching.

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Claude 3.7 Sonnet Tutorial

  1. Choose a Platform: Claude 3.7 Sonnet is accessible through the Claude.ai platform (supporting Web, iOS, and Android), the Anthropic API, Amazon Bedrock, and Google Cloud's Vertex AI. Users should choose the appropriate platform based on their needs and usage scenarios.
  2. Registration and Login: For first-time users, complete the registration process on the relevant platform and then log in to access the interface.
  3. Select Thinking Mode: Choose the appropriate thinking mode based on the complexity of the problem. For simpler questions, such as factual inquiries, select standard mode for quick responses; for complex problems, such as mathematical puzzles or programming tasks, select extended thinking mode.
  4. Input the Question: Clearly and accurately enter the question or instruction in the input box, such as "Help me write a Python script to implement data analysis functionality" or "Analyze the principle of this physics experiment."
  5. Obtain the Answer: The model will process the question based on the selected mode and input. After a short wait, the user will receive the answer. If dissatisfied with the answer or needing further discussion, continue asking questions or adjust the question phrasing.
  6. Adjust Thinking Budget (API Users): For API users, if specific requirements exist for answer quality and speed, the thinking time can be controlled by setting the thinking budget (number of tokens), specifying the relevant parameters in the request.

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Conclusion

The release of Claude 3.7 Sonnet and Claude Code represents significant advancements in the AI field. Claude 3.7 Sonnet, with its hybrid reasoning mode, powerful features, and broad applicability, offers users a transformative experience; Claude Code provides developers with an efficient coding assistance tool. They not only showcase Anthropic's innovative strength in AI technology but also drive the development of the entire AI industry.

However, AI technology continues to evolve, with many more possibilities awaiting exploration. If you encounter any novel findings, interesting experiences, or valuable suggestions during use, please share and discuss them in the comments section.