DeepSeek V4 Pro Launch Sparks Debate: Modest Gains, Strong Security

DeepSeek released the V4 Pro 0813 version around August 13, but official silence on social media sparked user speculation. Multiple evaluations show that this version offers marginal performance improvements in standard benchmarks, almost identical to July's V4-Flash-0731, and even scores lower in some tests like SciCode, leading developers to complain about incremental updates or a flop. However, V4 Pro shines in cybersecurity and coding capabilities: it ranks second among open-source models (1607 points) in Chatbot Arena's WebDev coding arena, and fifth in open-source for the text arena (1465 points). In vulnerability mining benchmarks, it topped the list with an 87.5% recall rate, despite having the lowest precision. Additionally, its single-task cost is only $0.14, making it 17 times cheaper than the higher-ranked Kimi K3. User tests revealed that V4 Pro discovered an RCE vulnerability in an open-source project within 30 minutes, showing significantly stronger security capabilities than the Flash version; however, some developers found V4 Flash beating the Pro version in Canvas coding tasks. Overall, while V4 Pro excels in security and coding, its limited general performance improvements and the contrast between the low-key release and evaluation data have sparked community debate.

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The release of DeepSeek V4 Pro has sparked discussions about incremental updates, but its breakthrough performance in security and coding, along with its extremely low cost, could alter the competitive landscape of open-source models. The contrast between the official low-profile attitude and community reviews also reflects the complexity of AI model evaluation and the gap in user expectations.

2026-08-13 ~ 2026-08-13 · 12 related posts

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