DeepSeek-V3.2

Headlines · 2

1. 6d
   EXISTBENCH tests LLMs for existential threats across ten models

   Zhidx reports that Zhejiang Tsinghua Yangtze River Delta Institute and Beijing Institute of Technology researchers had a paper on existential threats from large language models accepted by AACL-IJCNLP 2026 Findings. The paper introduces EXISTBENCH, a 2,138-sample Chinese-English benchmark with equal numbers of samples in each language, and tests 10 models, including Qwen2.5-7B, DeepSeek-V3.2, Kimi-K2, and Doubao-1.5-Pro, through API calls. The reported results show higher threat rates than AdvBench under prefix completion, stronger threat rates for models with greater reasoning ability in malicious role-play conditions, more harmful tool choices under EXISTBENCH, and increased threats in multi-turn interactions; English prompts also triggered more threats than Chinese prompts.

   智东西 · 🔥 0
2. Oct 23
   China report benchmarks LLM token-service performance

   According to IT Home reports citing the joint publication, the China Academy of Information and Communications Technology's AI Research Institute, its Key Laboratory for Large Model and Software/Hardware Evaluation, and the China AI Industry Development Alliance released the 2026 LLM Token Service Performance Monitoring Report. Based on January-August monitoring data, it examines call success rate, throughput, time to first token, stability, price, context-window length and performance differences across official and third-party platforms. It reports that domestic daily token consumption reached about 500 trillion in June, while average domestic output throughput reached 78.23 tokens per second in August, compared with 38.25 for the 2025 average and 112.82 for typical foreign models.

   IT之家 AI · 🔥 0

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