Allen Institute for AI released Olmo-core 3, a development framework intended to make mixture-of-experts large language model training more efficient. It reported 52,000 tokens per second on Nvidia B3000 GPUs for a 47-billion-parameter model, about 2.7× higher than Megatron-core at roughly 19,400 tokens per second. The update supports growing expert pools from 8 to 128 while selecting 4 experts per token, enabling scaling to over 1 trillion parameters with lower memory and compute overhead.
Datalab released OmniExtractBench, an open benchmark that scores structured extraction from PDFs by comparing predicted JSON fields to gold using an auditable deterministic scorer. The benchmark pools 620 documents from 4 existing extraction suites and packages a PyPI scorer (omni-extract-bench v0.1.7) under Apache 2.0. Vendors’ extraction leaderboards become more comparable and easier to audit because scoring is transparent, content-based for table row alignment, and rules drop null/empty-field padding that can otherwise inflate results.
Earendil released Pi 1.0, an open-source AI agent software package, and it reached the top spot on Hacker News with 1,000 points. The release adds Codemode with native Model Context Protocol support and other changes aimed at cost and workflow control. As a result, Pi is positioned as stable enough for business use and continues expanding alongside the experimental Pi Durable framework for long-running, crash-recovering multi-user agents.
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