Independent safety evaluation of DeepSeek V4.1 Flash-1017 reveals substantial improvements over prior versions and near-parity with leading closed-source models, while recommending process-level observability, incremental safety testing, and private benchmarks.
As frontier language models grow increasingly capable and autonomous, independent third-party evaluations are critical for characterizing their systemic safety risks. While closed-source releases are routinely accompanied by comprehensive system cards, open-weight models receive less scrutiny regarding frontier risks. To address this gap, we present an independent safety evaluation of DeepSeek V4.1 Flash-1017, the latest version of V4.1 Flash that departs from V4 with a new architecture, scaled-up training, and strong agentic capabilities. Drawing on the EU General-Purpose AI Code of Practice, we evaluate the model across 34 benchmarks, including 5 in-house suites, spanning evaluation…
systemic safety risksopen-weight modelsevaluation integrityloss of controlharmful manipulationreasoning tracesaction logsevaluation awarenessdata contaminationprivate benchmarks
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- Published
- Oct 26, 2026
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.