DeepSeek V4 targets mid-February launch with coding capabilities to challenge OpenAI and Anthropic

Insiders Say DeepSeek V4 Will Beat Claude and ChatGPT at Coding, Launch Within Weeks - Decrypt

Developers are already hyped ahead of a potential disruption. DeepSeek is reportedly planning to drop its V4 model around mid-February, and if internal tests are any indication, Silicon Valley's AI giants should be nervous. The Hangzhou-based AI startup could be targeting a release around February 17 -- Lunar New Year, naturally -- with a model specifically engineered for coding tasks, according to The Information. People with direct knowledge of the project claim V4 outperforms both Anthropic's Claude and OpenAI's GPT series in internal benchmarks, particularly when handling extremely long code prompts. Of course, no benchmark or information about the model has been publicly shared, so it is impossible to directly verify such claims. DeepSeek hasn't confirmed the rumors either. Still, the developer community isn't waiting for official word. Reddit's r/DeepSeek and r/LocalLLaMA are already heating up, users are stockpiling API credits, and enthusiasts on X have been quick to share their predictions that V4 could cement DeepSeek's position as the scrappy underdog that refuses to play by Silicon Valley's billion-dollar rules. This wouldn't be DeepSeek's first disruption. When the company released its R1 reasoning model in January 2025, it triggered a $1 trillion sell-off in global markets. The reason? DeepSeek's R1 matched OpenAI's o1 model on math and reasoning benchmarks despite reportedly costing just $6 million to develop -- roughly 68 times cheaper than what competitors were spending. Its V3 model later hit 90.2% on the MATH-500 benchmark, blowing past Claude's 78.3% and the recent update "V3.2 Speciale" improved its performance even more. V4's coding focus would be a strategic pivot. While R1 emphasized pure reasoning -- logic, math, formal proofs -- V4 is a hybrid model (reasoning and non-reasoning tasks) that targets the enterprise developer market where high-accuracy code generation translates directly to revenue. To claim dominance, V4 would need to beat Claude Opus 4.5, which currently holds the SWE-bench Verified record at 80.9%. But if DeepSeek's past launches are any guide, then this may not be impossible to achieve even with all the constraints a Chinese AI lab would face. Assuming the rumors are true, how can this small lab achieve such a feat? The company's secret weapon could be contained in its January 1 research paper: Manifold-Constrained Hyper-Connections, or mHC. Co-authored by founder Liang Wenfeng, the new training method addresses a fundamental problem in scaling large language models -- how to expand a model's capacity without it becoming unstable or exploding during training. Traditional AI architectures force all information through a single narrow pathway. mHC widens that pathway into multiple streams that can exchange information without causing training collapse. Wei Sun, principal analyst for AI at Counterpoint Research, called mHC a "striking breakthrough" in comments to Business Insider. The technique, she said, shows DeepSeek can "bypass compute bottlenecks and unlock leaps in intelligence," even with limited access to advanced chips due to U.S. export restrictions. Lian Jye Su, chief analyst at Omdia, noted that DeepSeek's willingness to publish its methods signals a "newfound confidence in the Chinese AI industry." The company's open-source approach has made it a darling among developers who see it as embodying what OpenAI used to be, before it pivoted to closed models and billion-dollar fundraising rounds. Not everyone is convinced. Some developers on Reddit complain that DeepSeek's reasoning models waste compute on simple tasks, while critics argue the company's benchmarks don't reflect real-world messiness. One Medium post titled "DeepSeek Sucks -- And I'm Done Pretending It Doesn't" went viral in April 2025, accusing the models of producing "boilerplate nonsense with bugs" and "hallucinated libraries." DeepSeek also carries baggage. Privacy concerns have plagued the company, with some governments banning DeepSeek's native app. The company's ties to China and questions about censorship in its models add geopolitical friction to technical debates. Still, the momentum is undeniable. Deepseek has been widely adopted in Asia, and if V4 delivers on its coding promises, then enterprise adoption in the West could follow. There's also the timing. According to Reuters, DeepSeek had originally planned to release its R2 model in May 2025, but extended the runway after founder Liang became dissatisfied with its performance. Now, with V4 reportedly targeting February and R2 potentially following in August, the company is moving at a pace that suggests urgency -- or confidence. Maybe both.

DeepSeek V4 and R2 launch timing stays hidden

Chinese AI unicorn DeepSeek is keeping the industry guessing regarding the release of its next-generation models, V4 and R2. Despite intense speculation about a potential launch during the upcoming Lunar New Year, the company has declined to comment on specific dates. Instead, the firm is letting its research do the talking. In recent weeks, DeepSeek has published multiple technical papers outlining novel methods to bypass current hardware limitations. With US sanctions restricting China's access to advanced Nvidia GPUs, DeepSeek's latest research focuses on algorithmic efficiency. On Tuesday, the company introduced "Engram," a conditional memory technique designed to solve GPU high-bandwidth memory shortages -- a critical bottleneck in scaling AI. This follows a paper co-authored by CEO Liang Wenfeng on "manifold-constrained hyper-connections" (mHC), a framework aimed at training massive systems more cost-effectively. Analysts believe these innovations are strategic moves to maintain momentum despite geopolitical headwinds. "DeepSeek just wants to prove that AI infrastructure innovation would drive efficiency," said Zhang Ruiwang, a Beijing-based information systems architect.

DeepSeek to launch new AI model focused on coding in February: Report

Chinese AI firm DeepSeek is reportedly preparing to release its new V4 model next month. This advanced AI is expected to excel in coding tasks, possibly surpassing competitors. A key feature is its ability to process very long coding instructions. This development could significantly benefit developers working on complex software projects. Chinese AI startup DeepSeek is expected to launch its ⁠next-generation AI model V4, featuring strong coding capabilities, in mid-February, The Information reported on Friday citing people familiar with the matter. Internal tests by DeepSeek employees suggested V4 could outperform rivals such as Anthropic's Claude and OpenAI's GPT series in coding tasks, the report said. The latest V4 model has also made breakthroughs in handling and processing extremely long coding prompts, a potential advantage for developers working on complex software projects, the Information added. Reuters could not immediately verify the report. DeepSeek did not immediately respond to a Reuters request for comment. Hangzhou-based startup DeepSeek has emerged as a key player in China's push to build its own AI ecosystem and bolster the domestic chip sector, drawing global attention after Silicon Valley ⁠executives praised ⁠its DeepSeek-V3 and DeepSeek-R1 models. Reuters previously reported that the Chinese artificial intelligence startup, which said in January it had built a low-cost rival to ChatGPT, has faced scrutiny in some countries over its security and privacy practices.

DeepSeek V4 Leaked : Coding-First Model Aims at Devs with New Memory & Reasoning AI

What if the next leap in AI wasn't just about generating code but about truly understanding it? Below, Universe of AI takes you through how the leaked details of DeepSeek V4 suggest a bold redefinition of what AI can achieve in software development. With its innovative Ingram architecture and a focus on long-context reasoning, this coding-first model promises to tackle challenges that have long frustrated developers, like maintaining coherence across sprawling codebases or reasoning through multi-file projects. If the leaks are accurate, DeepSeek V4 isn't just an upgrade; it's a statement of intent, directly challenging industry giants like GPT and Claude in their own domain. But what makes DeepSeek V4 truly intriguing is its dual-release strategy: a high-performance flagship edition for intensive coding tasks and a lighter, more accessible version for everyday development. This approach hints at a model designed not just for enterprise-scale teams but also for solo developers navigating complex workflows. From faster inference speeds to reduced GPU dependency, the leaked features suggest a model that could provide widespread access to AI-driven coding like never before. Could this be the moment where AI shifts from a helpful assistant to an indispensable partner in development? The implications are as exciting as they are fantastic. The decision to launch DeepSeek V4 during the Spring Festival appears to be a deliberate strategy to maximize visibility and market impact. According to insiders, the release will feature two distinct versions of the model: a flagship edition tailored for intensive coding tasks and a lighter, more responsive version designed for everyday development needs. This dual-release approach is expected to broaden the model's appeal, catering to both enterprise-level teams and individual developers. By aligning the launch with a globally recognized period of celebration and renewal, DeepSeek is positioning itself to capture the attention of a diverse audience. This timing could also provide an opportunity to showcase the model's capabilities in real-world scenarios, further solidifying its reputation as a practical and versatile tool. Early overviews indicate that DeepSeek V4 introduces significant advancements in coding-related tasks, positioning it as a strong contender in the AI development space. Internal testing has highlighted its ability to excel in critical areas, including: These features are particularly valuable for developers managing complex projects that require maintaining context and logical flow across multiple files. By integrating reasoning and general capabilities into a unified framework, DeepSeek V4 builds on the foundation laid by its predecessor, DeepSeek R1, while addressing its limitations. The model's ability to handle long-context reasoning and multi-file coherence makes it an invaluable tool for developers working on large-scale projects. These enhancements are expected to streamline workflows, reduce errors, and improve overall productivity. Dive deeper into DeepSeek with other articles and guides we have written below. At the heart of DeepSeek V4 lies the innovative Ingram architecture, which represents a significant evolution in AI model design. This architecture introduces a clear separation between memory and reasoning, allowing the model to operate more efficiently. The Ingram architecture employs a novel approach called "conditional memory via scalable lookup," which allows the model to retrieve knowledge stored in CPU RAM. By offloading static knowledge storage to CPUs, the model reduces its reliance on GPUs, resulting in lower operational costs and faster inference speeds. The dynamic computation layer, dedicated to reasoning, enhances the model's ability to tackle complex tasks such as: This architecture is particularly effective for long-context reasoning, a critical feature for developers working on extensive codebases. By maintaining coherence across large projects, DeepSeek V4 addresses one of the most significant challenges faced by existing AI models, offering a more reliable and efficient solution. Preliminary benchmarks suggest that DeepSeek V4 outperforms leading AI models in several key areas, thanks to its advanced architecture. The Ingram design has demonstrated superior results in: Internal evaluations also highlight improvements in reasoning, mathematical problem-solving, and overall coding efficiency. These advancements position DeepSeek V4 as a potential leader in the realm of AI-driven software development, offering tools that align closely with the needs of modern developers. DeepSeek V4's emphasis on coding-first functionality and cost efficiency could have far-reaching implications for the AI industry. By reducing GPU dependency and optimizing for software development tasks, the model makes high-performance AI tools more accessible to smaller teams and individual developers. This widespread access of AI technology could pressure competitors like OpenAI, Anthropic, and Google to rethink their strategies. The industry may witness a shift toward efficiency-focused designs and specialized applications, moving away from the traditional emphasis on brute-force scaling. Furthermore, DeepSeek V4's ability to handle complex, long-context tasks with precision could inspire a new wave of innovation in AI model design. Its focus on practical application and affordability sets a precedent for future developments, encouraging a more user-centric approach to AI technology. While the leaked details about DeepSeek V4 are promising, official confirmation from DeepSeek remains pending. If the overviewed capabilities are accurate, this model could establish a new benchmark for AI-driven coding and software development. For developers, DeepSeek V4 represents a potential turning point. Its tools are designed to address the specific challenges of modern software development, particularly in managing complex, multi-file projects and maintaining long-context coherence. As the February 2026 release date approaches, the tech industry is watching closely. DeepSeek V4 has the potential to not only outperform its competitors but also reshape the future of AI in coding and software development. Its success could mark a significant step forward in making advanced AI tools more accessible, efficient, and practical for a broader audience.

DeepSeek set to launch next-gen 'V4' model - The Information By Investing.com

Investing.com -- DeepSeek, the Chinese artificial intelligence upstart that rattled Silicon Valley and Wall Street last year, is preparing to launch its next-generation model in the coming weeks, according to a report from The Information. The new model, dubbed V4, is expected to feature advanced coding capabilities that internal tests suggest could leapfrog industry leaders, including OpenAI's GPT series and Anthropic's Claude. According to two people with direct knowledge of the matter cited by The Information, DeepSeek is targeting a release around the Lunar New Year in mid-February, though the timeline remains fluid. The timing of the anticipated launch follows a playbook that previously yielded massive cultural and market impact for the Beijing-based startup. Last year, DeepSeek released its flagship R1 model on January 20, just a week before China's weeklong Lunar New Year holiday. The move ensured the model dominated global tech discourse during a period of peak attention. DeepSeek, backed by the quantitative hedge fund High-Flyer Quant, became a global phenomenon following the release of R1. That "reasoning" model, designed to "think" through complex queries before answering, sent shockwaves through the AI sector not just for its performance, but for its efficiency. In a market where U.S. giants spend billions on compute, DeepSeek's ability to achieve comparable results at a fraction of the cost triggered a sharp reassessment of AI valuations and hardware dependency across Western markets. While DeepSeek's V3.2 model, released in December, reportedly outperformed OpenAI's GPT-5 and Google's Gemini 3.0 Pro on certain benchmarks, the company has yet to release a wholesale successor to its core architecture. The V4 model is positioned to fill that gap. The focus on coding is particularly significant. Programming proficiency is a primary benchmark for AI utility in enterprise environments, and a dominant V4 could further cement DeepSeek's position as a low-cost, high-performance alternative to American closed-source models. For investors, the impending release of V4 adds a new layer of volatility to the "AI arms race." When DeepSeek's R1 debuted last year, it caused a temporary rout in shares of U.S. chipmakers and AI frontrunners, as markets grappled with the reality of a Chinese player achieving parity with significantly less capital. As DeepSeek prepares to move from R1's reasoning breakthroughs to V4's coding-centric architecture, the industry is watching to see if the startup can once again disrupt the perceived dominance of San Francisco's AI titans.