趋近智
参数
-
上下文长度
400K
模态
Text
架构
Dense
许可证
Proprietary
发布日期
13 Nov 2025
训练数据截止日期
Sep 2024
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
GPT-5.1 No Thinking is a high-performance model variant designed for latency-sensitive applications that require the expansive knowledge and advanced instruction-following of the GPT-5 generation without the overhead of extended reasoning processes. By disabling the active chain-of-thought mechanism, this model provides direct, high-velocity responses suitable for interactive user interfaces and real-time data processing. It maintains a sophisticated modular architecture that leverages a sparse Mixture-of-Experts (MoE) design, ensuring that computational resources are allocated efficiently on a per-token basis.
Technically, the model employs a dense-to-sparse transition where a core language backbone is augmented by specialized expert layers. While the 'No Thinking' configuration restricts the model from generating intermediate reasoning tokens, it utilizes the same foundational weights as the reasoning-capable variants, preserving strong performance in structured tasks such as code generation and document extraction. This variant is specifically optimized for scenarios where deterministic execution and reduced time-to-first-token are prioritized over multi-step logical verification.
The model is integrated into the OpenAI API ecosystem as a configurable state of the flagship GPT-5.1 model, where developers can explicitly set the reasoning effort to a null value. This configuration is particularly effective for agentic workflows where a primary controller manages task decomposition and requires a fast, reliable execution unit for individual sub-tasks. It supports advanced features such as prompt caching with 24-hour retention and native tool-calling capabilities, making it a versatile component for complex software engineering and production-grade automation.
OpenAI's latest generation of language models featuring advanced reasoning capabilities, extended context windows up to 400K tokens, and specialized variants for coding, general intelligence, and efficiency. GPT-5 series introduces improved thinking modes, superior performance across benchmarks, and variants optimized for different use cases from high-capacity Pro models to efficient Nano models. Features native multimodal understanding, enhanced mathematical reasoning, and state-of-the-art coding abilities through Codex variants.
排名
#87
| 基准 | 分数 | 排名 |
|---|---|---|
Coding LiveBench Coding | 0.77 | 6 |
Agentic Coding LiveBench Agentic | 0.28 | 31 |
Data Analysis LiveBench Data Analysis | 0.64 | 39 |
Reasoning LiveBench Reasoning | 0.27 | 41 |
Mathematics LiveBench Mathematics | 0.45 | 44 |