The author investigates DeepSeek V4 Pro after a rumored release and sudden withdrawal, examining API errors, benchmark scores on AutomationBench and CyberGym, pricing versus V4 Flash, scaling limits, three practical demo cases, and the broader open‑source LLM landscape in China.
Kimi K3 is slated for a Q3 release with a massive 2.5 trillion parameters, surpassing DeepSeek V4 Pro and Baidu Wenxin 5.0, reigniting the large‑model arms race and prompting a debate between scale, efficiency, and ecosystem‑driven approaches.
Elon Musk announced that Grok 5 is AGI while xAI races through a month‑long rollout of Grok 4.3 (0.5 T), Grok 4.4 (1 T), Grok 4.5 (1.5 T) and a 6‑trillion‑parameter Grok 5, sparking intense debate over whether sheer scale can bridge the AGI gap.
Alibaba’s new QwQ‑32B large‑language model, with 32 billion parameters, delivers performance comparable to or surpassing the 671‑billion‑parameter DeepSeek‑R1 across math, coding, and general benchmarks, and is available via HuggingFace, ModelScope, and a DashScope API demo with example Python code.
