Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866912851801669632 |
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| author | Krishna, Satyapriya Memelli, Matteo Wang, Tong Mohanty, Abhinav Rajkumar, Claire O'Brien Motwani, Payal Gupta, Rahul Matsoukas, Spyros |
| author_facet | Krishna, Satyapriya Memelli, Matteo Wang, Tong Mohanty, Abhinav Rajkumar, Claire O'Brien Motwani, Payal Gupta, Rahul Matsoukas, Spyros |
| contents | Amazon published its Frontier Model Safety Framework (FMSF) as part of the Paris AI summit, following which we presented a report on Amazon's Premier model. In this report, we present an evaluation of Nova 2.0 Lite. Nova 2.0 Lite was made generally available from amongst the Nova 2.0 series and is one of its most capable reasoning models. The model processes text, images, and video with a context length of up to 1M tokens, enabling analysis of large codebases, documents, and videos in a single prompt. We present a comprehensive evaluation of Nova 2.0 Lite's critical risk profile under the FMSF. Evaluations target three high-risk domains-Chemical, Biological, Radiological and 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. We will continue to enhance our safety evaluation and mitigation pipelines as new risks and capabilities associated with frontier models are identified. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_19134 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework Krishna, Satyapriya Memelli, Matteo Wang, Tong Mohanty, Abhinav Rajkumar, Claire O'Brien Motwani, Payal Gupta, Rahul Matsoukas, Spyros Cryptography and Security Software Engineering Amazon published its Frontier Model Safety Framework (FMSF) as part of the Paris AI summit, following which we presented a report on Amazon's Premier model. In this report, we present an evaluation of Nova 2.0 Lite. Nova 2.0 Lite was made generally available from amongst the Nova 2.0 series and is one of its most capable reasoning models. The model processes text, images, and video with a context length of up to 1M tokens, enabling analysis of large codebases, documents, and videos in a single prompt. We present a comprehensive evaluation of Nova 2.0 Lite's critical risk profile under the FMSF. Evaluations target three high-risk domains-Chemical, Biological, Radiological and 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. We will continue to enhance our safety evaluation and mitigation pipelines as new risks and capabilities associated with frontier models are identified. |
| title | Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework |
| topic | Cryptography and Security Software Engineering |
| url | https://arxiv.org/abs/2601.19134 |