mlsanityData to 14 Oct 2026

Evaluating the Critical Risks of Amazon's Nova Premier under the Frontier Model Safety Framework

arXiv 2507.06260 ↗First posted 7 Jul 2025cs.CR cs.CYcited by 3

Not on the map. Why?

Abstract (arXiv)

Nova Premier is Amazon's most capable multimodal foundation model and teacher for model distillation. It processes text, images, and video with a one-million-token context window, enabling analysis of large codebases, 400-page documents, and 90-minute videos in a single prompt. We present the first comprehensive evaluation of Nova Premier's critical risk profile under the Frontier Model Safety Framework. Evaluations target three high-risk domains -- Chemical, Biological, Radiological & Nuclear (CBRN), Offensive Cyber Operations, and Automated AI R&D -- and combine automated benchmarks, expert red-teaming, and uplift studies to determine whether the model exceeds release thresholds. We summarize our methodology and report core findings. Based on this evaluation, we find that Nova Premier is safe for public release as per our commitments made at the 2025 Paris AI Safety Summit. We will continue to enhance our safety evaluation and mitigation pipelines as new risks and capabilities associated with frontier models are identified.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Jul 2025.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework
  2. 2025Quantifying CBRN Risk in Frontier Models
  3. 2026ForesightSafety Bench: A Frontier Risk Evaluation and Governance Framework towards Safe AI
  4. 2024Benchmark Early and Red Team Often: A Framework for Assessing and Managing Dual-Use Hazards of AI Foundation Models
  5. 2025Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
  6. 2025Safety Evaluation and Enhancement of DeepSeek Models in Chinese Contexts
  7. 2025A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety
  8. 2025Early External Safety Testing of OpenAI's o3-mini: Insights from the Pre-Deployment Evaluation