Post-Training
7 pieces on Post-Training.
News & Analysis
Adaption Labs Generates Training Data From a Task Description Alone
Adaption Labs' 'Invent a Dataset' creates structured training rows from plain-language descriptions—no seed corpus, schema, or labels required.
Z.ai GLM-5.3: Big Benchmark Gains from Post-Training Alone
Z.ai's GLM-5.3 reuses the 743B GLM-5.2 base model unchanged, delivering major gains on long-horizon coding and cybersecurity benchmarks through post-training scale alone.
Z.ai GLM-5.3: Frontier Gains From Post-Training Alone
GLM-5.3 reuses GLM-5.2's 743B base model unchanged. Terminal-Bench 3.0 jumps from 4.6 to 28.3; CyberGym hits 84.5%, edging past GPT-5.6 Sol.
Z.ai GLM-5.3: Post-Training Gains on a Fixed 743B Base Model
GLM-5.3 reuses GLM-5.2's 743B base unchanged. Terminal-Bench 3.0 jumps from 4.6 to 28.3; CyberGym hits 84.5%, edging closed frontier models.
Z.ai GLM-5.3: Frozen 743B Base, All Gains from Post-Training
Z.ai's GLM-5.3 reuses the frozen GLM-5.2 743B base model, extracting every benchmark gain through scaled post-training alone.
Z.ai GLM-5.3: Post-Training Gains on a Frozen 743B Base Model
Z.ai's GLM-5.3 reuses the GLM-5.2 base model unchanged, with all gains from scaled post-training — Terminal-Bench 3.0 jumps from 4.6 to 28.3.
Software Extraction Beats Hardware Acquisition at the AI Frontier
GLM-5.3, Kog, and Needle 2 show that post-training, bandwidth recovery, and compression outperform new compute spend in August 2026.