EMO

AstaBrief

Allen Institute for AI

AstaBrief is Ai2’s 8B scientific report-generation model, trained from Qwen3-8B with citation-focused supervised fine-tuning and direct preference optimization. It turns a research question and retrieved literature excerpts into a complete cited report in a single pass, and powers Asta’s Fast report mode. Ai2 releases the weights, training data, and a workflow for using local PDFs. The reported latency advantage evaluates the complete report pipeline rather than the checkpoint alone. Citation grounding is improved but does not guarantee that a synthesis preserves every study’s scope or conclusions.

BAR

Allen Institute for AI

BAR, or Branch-Adapt-Route, is Ai2’s released modular language-model family built from an Olmo 2 7B anchor and independently trained capability experts. Math, coding, tool-use, and safety experts are combined through a router into a final five-expert mixture, enabling capability updates without retraining the full model. The public checkpoints include the original anchor, intermediate two-expert combinations, and final combined model as variants. This is a concrete weight release supporting a post-training method, rather than a framework-only announcement. Expert merging and routing must be evaluated for interactions and task quality.

MolmoWeb

Allen Institute for AI

MolmoWeb is a released vision-language model trained for browser tasks from screenshots and natural-language instructions. Its 4B and 8B weights are distinct from the browser harness: the checkpoints generate textual reasoning, browser actions, and task-completion responses. Training uses MolmoWebMix, an open collection of synthetic and human browsing trajectories. Native and Transformers-compatible checkpoints are serving variants; compatibility fixes after launch do not establish a new model generation. Completing a web task depends on the external browser, observation/action interface, and execution permissions.