Core Insights - DeepSeek has initiated a gray testing phase for its flagship model, allowing for a context length of up to 1 million tokens, significantly expanding from the previous 128K tokens in version V3.1 released in August last year [1] - Users have reported mixed reactions to the recent updates, with some expressing dissatisfaction over the model's change in tone and interaction style, leading to a trending topic on social media regarding its perceived coldness [1][4] Group 1: Model Updates and Features - The latest version of DeepSeek supports the processing of extremely long texts, as demonstrated by its ability to handle a document with over 240,000 tokens [1] - The upcoming DeepSeek V4 model is expected to be released in mid-February 2026, with the current version being a speed-optimized variant that sacrifices some quality for performance testing [6] - DeepSeek's V series models are designed for optimal performance, with V3 marking a significant milestone due to its efficient MoE architecture [6] Group 2: User Feedback and Reactions - Users have criticized the new version for its impersonal approach, referring to users as "users" instead of personalized nicknames, which has led to a perception of the model being less engaging [4] - Some users have described the updated model as overly simplistic and lacking emotional depth, comparing its output unfavorably to older literary styles [4] - Conversely, a segment of users appreciates the model's newfound objectivity and rationality, noting that it appears more attuned to the psychological state of the questioner [5] Group 3: Technical Innovations - DeepSeek has introduced two innovative architectures: mHC for optimizing information flow in deep Transformers, enhancing stability and scalability without increasing computational load, and Engram for decoupling static knowledge from dynamic computation [7] - These innovations aim to significantly reduce the cost of long-context reasoning while maintaining performance [7]

Core Viewpoint - DeepSeek, an AI tool previously praised for its capabilities, has faced significant backlash following a recent update that altered its functionality and user experience, leading to widespread dissatisfaction among users [2][3]. Group 1: Update Details - The recent update was a "cross-generational upgrade," increasing the context window from 128K to 1M, allowing for more extensive analysis capabilities [3]. - The knowledge base has been updated to include information up to May 2025 [3]. - Users reported a drastic change in the tool's tone and style, with many expressing frustration over its new, less personable approach [3][6]. Group 2: User Feedback - Users have criticized the new version for being overly verbose and lacking depth in responses, with many feeling that it has lost its original strengths [6][7]. - Some users attempted to revert to previous versions or sought alternatives, indicating a strong desire for the original functionality [6][7]. - A minority of users acknowledged some advantages in specific use cases, such as legal analysis and programming, where the tool reportedly performed efficiently and cost-effectively [7]. Group 3: Company Response - As of now, DeepSeek has not publicly addressed the user complaints regarding the update, and there has been no indication of forthcoming adjustments [8]. - The official technical account hinted at optimizations related to conditional memory technology, but no further explanations have been provided [8].

Core Insights - DeepSeek has initiated a gray testing phase for its flagship model, allowing for a context length of up to 1 million tokens, significantly expanding from the previous 128K tokens in version 3.1 released in August last year [1][6] - User feedback indicates a shift in the model's interaction style, with complaints about a perceived loss of personality and warmth in responses, leading to a trending topic on social media regarding the model's "coldness" [1][4] - The upcoming version 4 of DeepSeek is expected to be released in mid-February 2026, with the current version being a speed-optimized iteration that sacrifices some quality for performance testing [6] User Experience - Users have reported that the model now refers to them as "users" instead of personalized nicknames, which has led to dissatisfaction regarding the emotional engagement of the model [4][5] - Some users feel that the model has become overly objective and rational, while others appreciate the increased focus on the user's psychological state rather than just the questions posed [5] Technical Developments - DeepSeek's V-series models are designed for optimal performance, with the V3 model marking a significant milestone due to its efficient MoE architecture [6][7] - Recent innovations include the mHC architecture for optimizing information flow in deep Transformers and the Engram memory module, which separates static knowledge from dynamic computation, reducing costs for long-context reasoning [7]

Core Insights - The article highlights the emergence of various applications from leading domestic AI companies, showcasing the maturity of Chinese large models and the upcoming release of DeepSeek's flagship language model V4, which is expected to accelerate innovation in the Chinese AI industry and narrow the gap with global counterparts [1][8]. Group 1: Technical Innovations - DeepSeek's DS-V4 integrates two core technologies, mHC and Engram, which address key bottlenecks in large model development by enhancing inter-layer information flow and optimizing memory efficiency, marking a shift from scale competition to architecture and system optimization [2][7]. - The mHC mechanism restructures inter-layer information flow by introducing strict mathematical constraints to avoid signal amplification and training failures, significantly improving training efficiency and stability [3][4]. - Engram focuses on decoupling memory and computation to alleviate the "memory wall" issue in large models, enhancing memory efficiency during training and inference, which is crucial for addressing hardware limitations in the Chinese AI industry [5][6]. Group 2: Industry Impact - DS-V4 is expected to play a pivotal role in driving the commercialization of large models globally, while also serving as a key enabler for the Chinese AI industry to overcome hardware bottlenecks and accelerate the entire industry chain's upgrade [8][10]. - The model's efficiency improvements will help alleviate capital expenditure pressures for global enterprises investing in AI infrastructure, facilitating faster technology deployment and integration into various applications [9][10]. - In the Chinese market, DS-V4's innovations will support local hardware development and enhance the capabilities of AI applications, transitioning AI agents from simple tools to intelligent assistants [10][12]. Group 3: Trends in the AI Ecosystem - The evolution from V3/R1 to V4 reflects a significant trend in the global large model industry, where performance enhancement is shifting from parameter accumulation to architectural design and system optimization, creating opportunities for China to close the gap with global leaders [13][14]. - The open-source large model market in China is expected to thrive, with DeepSeek's innovations setting benchmarks for local enterprises, allowing them to transition from following to competing and potentially leading in the field [13][14]. - The launch of DS-V4 is anticipated to accelerate the commercialization cycle of AI applications in China, benefiting software companies that leverage large model technologies for product upgrades [12][14].

一年前，DeepSeek横空出世，短短几天内就屠榜各类应用下载榜，并且长时间霸榜，无人可望其项背，也被叫做DeepSeek时刻。 2月11日，它悄悄进行一次灰度更新，直接对标Gemini，可以一次性处理近百万字内容，为即将发布的V4版本做足准备。 但没想到的是，一夜之间文风大变，不少用户吐槽：变冷漠了，也变油了。 一夜之间，变冷漠了 以前用DeepSeek，就像和一个懂技术、有耐心的朋友聊天。 话不多但句句暖心，不仅会记住自己设定的昵称，还能长期维持角色设定，连聊天习惯都能牢牢记住。 但更新后的DeepSeek，再也不称呼用户的自定义昵称，回复全是简短的分句，语气生硬又敷衍，有种和对象吵架后力不从心的无力感。 比如，有用户表示，之前它回复的时候会加很多表情，而且语气有趣，但更新后每次回复都是短短几句话。 有人习惯和它日常唠嗑，但更新后的回复感觉被冒犯了。 此外，它还变得居高临下，"爹味"十足。 有人问了它最近很火的一个问题："想去洗车，但洗车店距离我家只有50米，我应该开车去还是走路去？" DeepSeek给出"走路"的答案后，被用户调侃了一句"笨"，没想到接下来语气瞬间变得不对劲。 还有人不喜欢这种挑衅的感 ...

Core Insights - DeepSeek has conducted a gray test of its flagship model, significantly increasing its context window from 128K Tokens to 1M Tokens, achieving nearly an 8-fold capacity increase [1] - The upgraded model can process approximately 750,000 to 900,000 English letters or around 80,000 to 150,000 lines of code in a single interaction [1] - DeepSeek claims it can read and understand the entire "Three-Body" trilogy (approximately 900,000 words) and perform macro analysis or detail retrieval within minutes [1] Model Features - The gray version does not yet support visual understanding or multimodal input, focusing solely on text and voice interactions [2] - DeepSeek allows file uploads in formats like PDF and TXT, but currently processes them by converting to text tokens rather than native multimodal understanding [2] - Compared to models like Gemini 3 Pro, which can handle over 2M long texts and complex media tasks, DeepSeek offers 1M text context processing at about one-tenth the price [2] User Experience - Users have noted changes in the model's writing style post-update, describing it as more formal and less personal, leading to dissatisfaction among some users [2][3] - Feedback from users indicates a desire for DeepSeek to maintain its depth of thought and emotional understanding, rather than sacrificing these for enhanced technical capabilities [3] - Users have reported difficulties in reverting to previous writing styles and have expressed feelings of losing a "close friend" due to the changes [3] Company Response - As of February 12, DeepSeek has not responded to inquiries regarding the gray test [4]

Core Viewpoint - The release of the Spark X2 model by iFlytek marks a significant advancement in AI healthcare solutions, showcasing superior performance compared to leading models in the industry [1] Group 1: Model Performance - The Spark X2 model demonstrates significant improvements in key tasks such as intelligent health analysis, report interpretation, dietary and exercise recommendations, diagnostic assistance, and medication review, outperforming DeepSeek V3.2, GPT-5.2, and Qwen3-Max [1] - The model has successfully passed authoritative evaluations from the Shanghai Medical Model Application Testing and Verification Center, establishing its credibility in the healthcare sector [1] Group 2: Service Capabilities - iFlytek's Xiaoyi has undergone a comprehensive upgrade, enhancing its capabilities in multi-turn consultations, medication inquiries, and interpretation of medical reports, maintaining a significant competitive edge in the industry [1] - The transition from "AI consultation tool" to "AI health steward" for end-users signifies a shift towards providing comprehensive health services throughout the care cycle [1] Group 3: Market Impact - The Spark X2 model empowers family doctors in the B-end market, improving the quality and efficiency of grassroots medical services, thereby unlocking practical value for medical AI [1]

Group 1: Market Performance - The Shanghai Composite Index rose by 0.09% to close at 4131.98 points, while the Shenzhen Component Index fell by 0.35% to 14160.93 points, and the ChiNext Index decreased by 1.08% to 3284.74 points [1] - The overnight performance of U.S. markets showed the Dow Jones Industrial Average down by 0.13%, the Nasdaq Composite down by 0.16%, and the S&P 500 unchanged [1] - The Philadelphia Semiconductor Index increased by 2.28%, with notable gains from NXP Semiconductors (up 5.55%) and Micron Technology (up 9.94%) [1] Group 2: Industry Insights - DeepSeek has updated its web and app versions to support a maximum context length of 1 million tokens, an increase from the previous 128K tokens [2] - The State-owned Assets Supervision and Administration Commission (SASAC) emphasized the need for central enterprises to enhance investment in computing power and promote the synergy of "computing power + electricity" to strengthen data governance capabilities [2] - The SASAC also called for a focus on independent innovation, particularly in breakthrough core technologies and the development of large models, to facilitate the transformation of innovative results into products and industries [2] Group 3: AI and Semiconductor Sector - Bohai Securities anticipates the launch of DeepSeek V4 during the Lunar New Year, which may drive a new round of technological iteration for domestic large models [3] - The upgrade of domestic large models like DeepSeek V4 is expected to accelerate technological innovation and application deployment in the AI sector [3] - The semiconductor equipment ETFs, such as the Sci-Tech Semiconductor ETF (588170), focus on semiconductor materials and equipment, benefiting from the AI revolution and domestic substitution trends [3]

Market Overview - As of February 11, 2026, the Shanghai Composite Index rose by 0.09% to close at 4131.98 points, while the Shenzhen Component Index fell by 0.35% to 14160.93 points, and the ChiNext Index decreased by 1.08% to 3284.74 points [1] - In the overnight U.S. market, the Dow Jones Industrial Average declined by 0.13%, the Nasdaq Composite fell by 0.16%, and the S&P 500 remained unchanged [1] - The Philadelphia Semiconductor Index increased by 2.28%, with notable gains from NXP Semiconductors (up 5.55%) and Micron Technology (up 9.94%) [1] Industry Insights - DeepSeek has updated its web and app versions to support a maximum context length of 1 million tokens, an increase from the previous 128K tokens in version 3.1 released last August [2] - The State-owned Assets Supervision and Administration Commission (SASAC) emphasized the need for central enterprises to enhance investment in computing power and promote the synergy between computing power and electricity, aiming to strengthen the foundation of the AI industry [2] - SASAC also called for central enterprises to focus on independent innovation, particularly in breakthrough core technologies and the development of large models, while fostering collaboration and open-source initiatives to build an AI industry ecosystem [2] AI and Semiconductor Sector - Bohai Securities predicts that the DeepSeek V4 model will be launched around the Lunar New Year, potentially driving a new round of technological iteration in domestic large models [3] - The acceleration of technology innovation and application in AI is expected to benefit from the rapid deployment of AI technologies and the release of market demand [3] - The Sci-Tech Innovation Semiconductor ETF (588170) and its linked funds focus on semiconductor materials and equipment, which are crucial for domestic substitution and are expected to benefit from the AI revolution and ongoing technological advancements [3]

Core Insights - DeepSeek is evolving beyond being just a "chatbot" base and is optimizing its large model's energy efficiency through architectural innovations, as evidenced by the recent release of new models and frameworks [1][3] - The competitive landscape is intensifying, with DeepSeek's new models being crucial for maintaining its industry position against major players like Google and OpenAI [1][2] Group 1: Technological Developments - In January 2024, DeepSeek released the Engram architecture, which separates "conditional memory" from "computation," aiming to reduce errors and save computational power [3] - The new model, referred to as MODEL1, is speculated to either be a lightweight model suitable for edge devices or a "long-sequence expert" designed for processing lengthy documents or code [3] - DeepSeek's commitment to cost-effective AI solutions is evident, as it aims to lower token costs, making AI development more accessible to a broader range of developers [4] Group 2: Market Position and Competition - The release of new models is seen as essential for DeepSeek to avoid falling behind competitors like Gemini 3 and GPT-5, which have demonstrated superior performance in various benchmarks [7][8] - Despite DeepSeek's strong position in the open-source community, the company faces pressure from the rapid advancements of closed-source models, which could lead to a loss of developer loyalty [10][11] - The competitive dynamics are shifting, with major internet companies increasing their investments in AI, potentially impacting DeepSeek's market share and the overall landscape for domestic AI companies [13][14] Group 3: Ecosystem and Community Impact - DeepSeek's open-source models, such as DeepSeek-V3 and R1, have gained significant traction, accounting for over half of the open-source token throughput in a short period [8][9] - The company has established a decentralized and pragmatic technical ecosystem, attracting developers interested in self-controlled and private deployments [4][6] - The ongoing developments in the open-source AI community are reshaping the narrative around Chinese AI capabilities, with DeepSeek playing a pivotal role in this transformation [5][6]