Ai2 open-sources AstaBrief, a research-report model that can run locally and averages about 51 seconds per cited report
Ai2 open-sourced AstaBrief 8B, a small model that turns a research question and retrieved literature excerpts into a cited report, releasing the weights and training data. It already runs as Fast mode in Asta’s Generate a report feature; Ai2 says the full pipeline averages 51.1 seconds per report, about 3.5× faster than the Claude-powered Thinking mode (178.5 seconds).
Ai2 says AstaBrief starts from Qwen3-8B and that most of the work went into post-training data: from about ninety thousand real research queries, it generated about forty-seven thousand supervised fine-tuning examples with several proprietary models, then built about six thousand preference pairs for DPO. The biggest gain came from filtering out synthetic reports with low citation density; the model writes the full report in one pass rather than section by section.
Open weights let institutions deploy it on their own hardware, behind their own firewall, without sending unpublished or sensitive research questions to a proprietary model API; Ai2 also provides an example workflow for generating reports from your own PDFs.
Ai2 notes the limits: most training and evaluation was completed in 2025, so the proprietary comparison models reflect the frontier at that time, and it has not rerun the full evaluation against current frontier models. In a small 14-question human study, DR Tulu won on overall preference, while two of the three researchers preferred AstaBrief on citation accuracy.