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分类：DeepSeek

DeepSeek专栏深度解析这一领先开源AI模型系列的核心优势。涵盖DeepSeek-V4、V3.2、MODEL1等最新模型动态，深度探讨DeepGEMM矩阵运算优化技术及其在Hopper GPU上的性能表现。提供从官网使用到API集成、智能体开发及论文写作的完整指南，助您掌握这一国产高性能大模型的权威技术解析与最佳实践。

共 79 篇
DeepSeek-V4代码生成模型如何？2026年发布参数性能全解析

DeepSeek-V4代码生成模型如何？2026年发布参数性能全解析

AIAI Insight
DeepSeek-V4 is a next-generation large language model developed by DeepSeek, specializing in code generation with 671B parameters and 37B active inference parameters. It features a 1M token context window, native multimodal reasoning, and is scheduled for release around the 2026 Lunar New Year, with internal benchmarks showing superior programming performance compared to Claude and GPT models. 原文翻译： DeepSeek-V4 是深度求索公司开发的下一代大语言模型，专注于代码生成，拥有6710亿总参数和370亿推理激活参数。该模型具备100万tokens上下文窗口和原生多模态推理能力，计划于2026年农历新年前后发布。内部基准测试显示，其在编程任务上的表现优于Claude和GPT系列模型。
DeepSeek2026/3/3
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DeepSeek AI助手是什么？2026年最新功能模型全解析

DeepSeek AI助手是什么？2026年最新功能模型全解析

AIAI Insight
DeepSeek is an advanced AI assistant powered by cutting-edge language models, offering capabilities in programming, data analysis, creative writing, and problem-solving. It provides multiple specialized models including DeepSeek-R1 for complex reasoning, DeepSeek-V3 for general AI tasks, and DeepSeek-Coder for programming optimization, available through web interface, mobile app, and API integration. 原文翻译： DeepSeek是一款由尖端语言模型驱动的高级AI助手，具备编程、数据分析、创意写作和问题解决等多种能力。它提供多个专业模型，包括用于复杂推理的DeepSeek-R1、通用AI任务的DeepSeek-V3以及编程优化的DeepSeek-Coder，可通过网页界面、移动应用和API集成使用。
DeepSeek2026/3/3
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DeepSeek是否从GPT蒸馏而来？2026知识蒸馏技术分析

DeepSeek是否从GPT蒸馏而来？2026知识蒸馏技术分析

AIAI Insight
Knowledge distillation is a model training technique where a smaller student model learns from a larger teacher model, improving efficiency while maintaining performance. This article analyzes whether DeepSeek models were distilled from GPT, examining data, logits, and feature distillation methods. (知识蒸馏是一种模型训练技术，通过教师-学生架构让小模型从大模型中学习知识，在提升效率的同时保持性能。本文深入分析DeepSeek是否从GPT蒸馏而来，探讨数据蒸馏、Logits蒸馏和特征蒸馏三种方法。)
DeepSeek2026/2/16
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FlashMLA：DeepSeek为Hopper GPU打造的高性能注意力解码内核

FlashMLA：DeepSeek为Hopper GPU打造的高性能注意力解码内核

AIAI Insight
FlashMLA is an optimized MLA decoding kernel for Hopper GPUs that significantly improves LLM inference efficiency through advanced attention mechanisms and memory optimization. (FlashMLA是专为Hopper GPU优化的MLA解码内核，通过先进的注意力机制和内存优化显著提升大语言模型推理效率。)
DeepSeek2026/1/24
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DeepSeek V4前瞻：代码提交揭示下一代AI模型的架构革新与编程能力飞跃

DeepSeek V4前瞻：代码提交揭示下一代AI模型的架构革新与编程能力飞跃

AIAI Insight
DeepSeek is reportedly developing a new flagship AI model, DeepSeek V4, with enhanced coding capabilities, set to launch around Chinese New Year in mid-February. Recent GitHub code updates reveal a new model identifier "MODEL1" with distinct technical features including KV cache layout, sparsity handling, and FP8 decoding support, suggesting optimized memory and computational efficiency. The model may also incorporate recent research on optimized residual connections and biologically-inspired AI memory modules. (DeepSeek据称正在开发新一代旗舰AI模型DeepSeek V4，具备更强的编程能力，计划于2月中旬农历新年期间发布。近期GitHub代码更新显示新的模型标识符“MODEL1”具有独特技术特征，包括键值缓存布局、稀疏性处理和FP8解码支持，表明在内存优化和计算效率方面进行了针对性设计。该模型可能整合优化残差连接和受生物学启发的AI记忆模块等最新研究成果。)
DeepSeek2026/1/24
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DeepSeek发布FlashMLA：专为Hopper GPU优化的高效MLA解码内核，AI推理性能大幅提升

DeepSeek发布FlashMLA：专为Hopper GPU优化的高效MLA解码内核，AI推理性能大幅提升

AIAI Insight
FlashMLA is an efficient MLA decoding kernel optimized for NVIDIA Hopper GPUs, delivering up to 3000 GB/s memory bandwidth and 580 TFLOPS compute performance while reducing KV cache requirements by 93.3% for faster, more cost-effective AI inference. (FlashMLA是DeepSeek针对NVIDIA Hopper GPU优化的高效MLA解码内核，在内存受限配置下可达3000 GB/s带宽，计算受限配置下可达580 TFLOPS峰值性能，同时将KV缓存需求减少93.3%，实现更快、更经济的AI推理。)
DeepSeek2026/1/23
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DeepSeek FlashMLA代码分析：揭秘未公开的MODEL1高效推理架构

DeepSeek FlashMLA代码分析：揭秘未公开的MODEL1高效推理架构

AIAI Insight
DeepSeek's FlashMLA repository reveals two distinct model architectures: V3.2 optimized for maximum performance and precision, and MODEL1 designed for efficiency and deployability with lower memory footprint and specialized long-sequence handling. (DeepSeek的FlashMLA代码库揭示了两种不同的模型架构：V3.2针对最大性能和精度优化，而MODEL1则针对效率和可部署性设计，具有更低的内存占用和专门的长序列处理能力。)
DeepSeek2026/1/23
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FlashMLA：DeepSeek开源的高效MLA解码内核，专为NVIDIA Hopper GPU优化

FlashMLA：DeepSeek开源的高效MLA解码内核，专为NVIDIA Hopper GPU优化

AIAI Insight
FlashMLA is an open-source, high-performance Multi-Head Linear Attention (MLA) decoding kernel optimized for NVIDIA Hopper architecture GPUs, designed to handle variable-length sequences efficiently. It enhances memory and computational efficiency through optimized KV caching and BF16 data format support, achieving up to 3000 GB/s memory bandwidth and 580 TFLOPS computational performance on H800 SXM5 GPUs. FlashMLA is ideal for large language model (LLM) inference and natural language processing (NLP) tasks requiring efficient decoding. (FlashMLA是DeepSeek开源的高效MLA解码内核，专为NVIDIA Hopper架构GPU优化，用于处理可变长度序列。通过优化KV缓存和采用BF16数据格式，提升了内存和计算效率，在H800 SXM5 GPU上内存带宽可达3000 GB/s，计算性能可达580 TFLOPS。适用于大语言模型推理和需要高效解码的自然语言处理任务。)
DeepSeek2026/1/23
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FlashMLA：DeepSeek高性能注意力内核库，驱动V3模型实现660 TFLOPS

FlashMLA：DeepSeek高性能注意力内核库，驱动V3模型实现660 TFLOPS

AIAI Insight
FlashMLA is DeepSeek's optimized attention kernel library that powers DeepSeek-V3 models, featuring token-level sparse attention with FP8 KV cache support, achieving up to 660 TFLOPS performance on NVIDIA H800 GPUs. (FlashMLA是DeepSeek优化的注意力内核库，为DeepSeek-V3模型提供动力，具有令牌级稀疏注意力和FP8 KV缓存支持，在NVIDIA H800 GPU上实现高达660 TFLOPS的性能。)
DeepSeek2026/1/23
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