Full GLM-5.3 (753B) on 4× DGX Spark ran the Tower of Babel Bench: one brief, then 6 hours of active time with no human to answer questions. The task: build the Tower of Babel in Blender "in extreme, exquisite detail" and host a web app showing its progress. What it did on its own: -planned milestones with time boxes and kept a dated journal -wrote the whole scene as procedural Python: 2,378 objects, 340 unique meshes, 128k faces -rendered low-res drafts to check its work, then four 1920×1080 Cycles finals -built and hosted its own web app: renders, 3D viewer, history, plan, live stats It also realized it had no vision, so it wrote a tool that turns its renders into ASCII brightness maps to "see" them. @matdmiller bench isn't "can it write code." It tests: -endurance: working hours alone and pacing against a clock -time management: slow renders in the background, no waiting around -context management: 262K window, compaction, helper agents -3D/spatial reasoning, coding and the final quality Every call, token, tool use and cache hit is logged. The run: -6:00 active hours, 0 crashes, 0 errors -274 model calls -178,868 tokens generated (97,653 reasoning) -10.36M prompt tokens, 92.3% served from cache -4 finals, 53–168 s each on CPU GLM-5.3 EXL3 2.75bpw · TensorFold TP4 (@u1tra_instinct image) · 262K context