Chinese AI startup DeepSeek is reportedly preparing to launch its V4 large language model around February 17, 2026, with insiders claiming it will outperform leading competitors like OpenAI's ChatGPT and Anthropic's Claude on long-context coding tasks. According to sources cited by The Information, internal benchmarks show V4 surpassing these Silicon Valley giants specifically in handling extensive code prompts, though no public benchmarks or official confirmation from DeepSeek has been provided.
The developer community is already buzzing with anticipation. Social platforms like Reddit's r/DeepSeek and r/LocalLLaMA are active with discussions, while users are stockpiling API credits in preparation. AI developer Yuchen Jin noted on X that "DeepSeek V4 is rumored to drop soon, with stronger coding than Claude and GPT," adding that recent restrictions by Anthropic on third-party app access are pushing labs to accelerate their coding model development.
This launch represents a strategic pivot for DeepSeek. While its previous R1 model (released January 2025) focused on pure reasoning—matching OpenAI's o1 on math and reasoning benchmarks at a fraction of the cost—V4 is designed as a hybrid model combining reasoning and non-reasoning tasks. It specifically 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's current SWE-bench Verified record of 80.9% accuracy.
The company's potential breakthrough stems from a new training method called Manifold-Constrained Hyper-Connections (mHC), detailed in a January 1 research paper co-authored by founder Liang Wenfeng. This technique addresses scaling instability in large language models by creating multiple information pathways instead of forcing all data through a single narrow channel. Analysts have called mHC a "striking breakthrough" that could help DeepSeek bypass compute bottlenecks despite U.S. chip export restrictions.
DeepSeek's previous releases have demonstrated significant impact. The R1 model triggered a $1 trillion sell-off in global markets when it matched premium models despite costing only $6 million to develop—approximately 68 times cheaper than competitors. The V3 model later achieved 90.2% on the MATH-500 benchmark, surpassing Claude's 78.3%. The company has gained substantial traction, commanding 89% of China's AI market according to Microsoft and growing adoption in developing countries.
However, DeepSeek faces skepticism and challenges. Some developers complain about inefficiencies in reasoning models, while critics question whether benchmarks reflect real-world performance. The company also contends with privacy concerns, geopolitical friction due to its Chinese origins, and questions about potential censorship in its models.
The timing suggests urgency or confidence—or both. DeepSeek reportedly postponed its R2 model from May 2025 after founder Liang was dissatisfied with performance, with R2 now potentially following V4 in August 2026. If V4 delivers on its coding promises, it could accelerate enterprise adoption in Western markets and further disrupt the global AI landscape.
