DeepSeek
DeepSeek API 官方文档：2026年开发者集成指南与核心功能详解
DeepSeek API provides comprehensive documentation for developers to integrate advanced AI capabilities, including chat completions, function calling, and JSON output, with detailed guides on authentication, pricing, and best practices.
原文翻译：
DeepSeek API 为开发者提供全面的文档，用于集成高级AI功能，包括对话补全、函数调用和JSON输出，并包含认证、定价和最佳实践的详细指南。
2026/3/5
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DeepSeek-V3.2推理模型如何免费使用？2026年AI智能体开发指南
DeepSeek has launched its latest reasoning-first model, DeepSeek-V3.2, designed specifically for AI agents, now accessible via web, mobile app, and API with free access available.
原文翻译：
DeepSeek已发布其最新的推理优先模型DeepSeek-V3.2，专为AI智能体设计，现可通过网页、移动应用和API访问，并提供免费使用。
2026/3/5
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如何使用DeepSeek AI写论文？2026年最新指令模板全攻略
This comprehensive guide provides step-by-step instructions for using DeepSeek AI to streamline academic paper writing, covering everything from registration and framework building to content generation, optimization, and final checks. It includes tested command templates for each stage of the writing process, helping researchers and students save significant time while maintaining academic rigor.
原文翻译：
本指南详细介绍了使用DeepSeek AI简化学术论文写作的步骤，涵盖从注册、框架搭建到内容生成、优化和最终检查的全过程。包含每个写作阶段经过测试的指令模板，帮助研究人员和学生节省大量时间，同时保持学术严谨性。
2026/3/4
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DeepSeek-V4代码生成模型如何？2026年发布参数性能全解析
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。
2026/3/3
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DeepSeek AI助手是什么？2026年最新功能模型全解析
DeepSeek 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。
2026/3/3
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DeepSeek V3.2模型发布：2026年AI智能体与推理能力全面升级
DeepSeek has released its V3.2 flagship model with enhanced agent capabilities and reasoning integration, available across web, mobile app, and API platforms.
原文翻译：
深度求索发布了V3.2旗舰模型，强化了Agent能力和思考推理功能，已在网页端、移动应用和API平台全面上线。
2026/3/2
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DeepSeek是否从GPT蒸馏而来？2026知识蒸馏技术分析
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。)
2026/2/16
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FlashMLA：DeepSeek为Hopper GPU打造的高性能注意力解码内核
FlashMLA 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。)
2026/1/24
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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 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。)
2026/1/24
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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
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。)
2026/1/23
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