趋近智
参数
-
上下文长度
200K
模态
Text
架构
Dense
许可证
Proprietary
发布日期
29 Sept 2025
训练数据截止日期
Jan 2025
注意力结构
Multi-Head Attention
隐藏维度大小
-
层数
-
注意力头
-
键值头
-
激活函数
-
归一化
-
位置嵌入
Absolute Position Embedding
Claude 4.5 Sonnet is a mid-tier frontier model engineered by Anthropic to deliver a refined equilibrium between high-order reasoning and operational efficiency. Designed as a production workhorse, it is specifically optimized for complex agentic workflows, large-scale software engineering, and sophisticated computer-use tasks. The model serves as a core component for autonomous systems, supporting long-running operations with a significant emphasis on reliability and instruction-following accuracy across diverse professional domains.
The underlying architecture utilizes a dense transformer-based framework that integrates a hybrid reasoning system. This system allows for two distinct modes of execution: a standard low-latency mode for rapid interaction and an extended thinking mode that exposes the model's internal reasoning process for more difficult problem-solving. It features a substantial 200,000-token context window for general availability, with a specialized 1-million-token beta capacity for handling massive datasets, entire codebases, or extensive research documentation. The implementation of absolute position embeddings and multi-head attention ensures stable performance over these long sequences.
Technically, the model introduces advanced capabilities such as parallel tool execution, which enables agents to perform multiple actions, such as executing several shell commands simultaneously, within a single turn. It is natively integrated with the Model Context Protocol (MCP) and supports specific developer tools like checkpoints for state management and context editing for precise memory control. These features make it particularly suitable for enterprise-grade applications in finance, law, and cybersecurity, where sustained focus and deep domain knowledge are required for multi-step, high-stakes tasks.
Enhanced Claude models with further improvements in reasoning, coding, and agentic capabilities. Features advanced thinking modes with adjustable effort levels (high, medium, standard) for optimal performance-latency tradeoffs. Excels at complex analysis, software development, web development, and long-context understanding. Includes thinking variants that expose reasoning process for improved transparency.
排名
#40
| 基准 | 分数 | 排名 |
|---|---|---|
Web Development WebDev Arena | 1450 | ⭐ 7 |
Coding LiveBench Coding | 0.76 | 9 |
Graduate-Level QA GPQA | 0.83 | 10 |
Agentic Coding LiveBench Agentic | 0.48 | 12 |
Data Analysis LiveBench Data Analysis | 0.67 | 29 |
Reasoning LiveBench Reasoning | 0.42 | 32 |
Mathematics LiveBench Mathematics | 0.63 | 37 |