GLM-4.5-Air midtrain (swe50-star50, ~90B tokens)
Continued pretraining ("midtrain") of zai-org/GLM-4.5-Air-Base on a 50/50 mixture of
SWE-agent-trajectory tokens (SWE-ZERO OSS trajectories + own distillation) and
StarCoder-v2-anchored code / math / STEM / web text (dolmino mix, nemotron-cc-math).
184 train datasets; 16k sequence length; trained for 19,160 steps.
This is the initialization checkpoint used by the downstream SFT-v3 -> RL pipeline
(the "bigrun"). At matched SFT steps, initializing from this checkpoint instead of the
raw base improved SWE-bench-Verified by +6 to +9 points.
- Full data recipe (all 184 datasets and weights): see the accompanying configs release.
- Midtrain author: Wai Tong Chung. Released as part of a Duke University research project.