ZGCM-1: a fully open, extremely efficient 7B foundation model for math and agentic search
ZGCAGI
A fully open 7B dense model trained from scratch that matches much larger frontier models (Qwen3-235B, GLM-5.1) on math reasoning and agentic search by combining deliberate internal reasoning with active tool use over a 256K context. Includes a stable FP8 Muon optimizer, MDP-formulated mid-training, agent swarms managing the R&D workflow, and a full release of weights, checkpoints, code, data and recipes.
Why it matters
291 upvotes on HF Daily Papers; unusually complete open-source release of the entire training pipeline, with a 4.2x pre-training efficiency gain and eight distilled empirical findings.
Importance: 4/5
Notable paper + 291 upvotes on HF Daily Papers (+1 bump)