DeepSeek V4 is rumored to outperform ChatGPT and Claude in long-context coding, targeting elite-level coding tasks. Insiders claim that Silicon Valley’s AI landscape should be concerned if internal tests hint at its expected performance after the rollout in mid-February.
Chinese-based AI start-up DeepSeek is reportedly planning to release DeepSeek V4, its latest large language model, on February 17. People familiar with the matter claim that the model is poised to cast a shadow over existing large language models, such as OpenAI’s ChatGPT and Anthropic’s Claude, when handling long-context code prompts and tasks.
Developers express deep anticipation for the DeepSeek V4 release
The Chinese company has not publicly disclosed any information about the imminent release or confirmed the rumors as of the time of writing. Developers across different social networks have expressed deep anticipation for the release. Yuchen Jin, an AI developer and co-founder of Hyperbolic Labs, wrote on X that “DeepSeek V4 is rumored to drop soon, with stronger coding than Claude and GPT.”
Subreddit r/DeepSeek also heated up, with one user explaining that their obsession with DeepSeek’s imminent V4 model was not normal. The user said that they frequently “check news, possible rumors, and I even go to read the Docs on the DS website to look for any changes or signs that indicate an update.”
DeepSeek’s previous releases have had a significant impact on global markets. The Chinese AI start-up released its R1 reasoning model in January 2025, leading to a trillion-dollar sell-off. The release matched OpenAI’s 01 model on math and reasoning benchmarks, despite costing significantly less than the US AI startup spent on its 01 model.
The Chinese company reportedly spent only $6 million on the model release. Meanwhile, global competitors spend nearly 70 times more for the same output. Its V3 model also logged a 90.2% score on the MATH-500 benchmark, compared to Claude’s 78.3%. DeepSeek’s more recent V3 upgrade (V3.2 Speciale) further improved its productivity.
Its V4 model’s selling point has evolved from the V3’s emphasis on pure reasoning, formal proofs, and logical math. The new release is expected to be a hybrid model that combines both reasoning and non-reasoning tasks. The model aims to capture the developer market by filling an existing gap that demands high accuracy and long-context code generation.
Claude Opus 4.5 currently claims dominance in the SWE benchmark, achieving an accuracy of 80.9%. The V4 needs to beat this to overturn Claude Opus 4.5. Based on previous successes, the incoming model may surpass this threshold and claim dominance in the benchmark.
DeepSeek pioneers mHC for training LLMs
DeepSeek’s success has left many in profound professional disbelief. How could such a small company achieve such milestones? The secret could be deeply entrenched in its research paper published on January 1. The company identified a new training method that allows developers to easily scale large language models. Liang Wenfeng, founder and CEO of DeepSeek, wrote in the research that the company is using Manifold-Constrained Hyper-Connections (mHC) to train its AI models.
The executive proposed using mHC to address the issues encountered when developers train large language models. According to Wenfeng, mHC is an upgrade of Hyper-Connections (HC), a framework that other AI developers use to train their large language models. He explained that HC and other traditional AI architectures force all data through a single, narrow channel. At the same time, mHC widens that pathway into multiple channels, facilitating the transfer of data and information without causing training collapse.
Lian Jye Su, chief analyst at Omdia, commended CEO Wenfeng for publishing their research. Su emphasized that DeepSeek’s decision to publish its training methods dictates renewed confidence in the Chinese AI sector. DeepSeek has dominated the developing world. Microsoft published a report on Thursday, showing that DeepSeek commands 89% of China’s AI market and has been gaining momentum in developing countries.
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