=== START 11:30:00
               총계         사용        여분      공유    버퍼/캐시    가용
메모리:          121           6         115           0           0         114
ds4: Linux cuda backend set oom_score_adj=1000
ds4: CUDA backend initialized on NVIDIA GB10 (sm_121) dev=0
ds4: SSD streaming mixed-precision model: 10/43 routed layers off the slab size class will bypass the expert cache and read experts via mapped model views
ds4: SSD streaming initial cuda model map restricted to token embedding (1 spans, 0.99 GiB tensor span)
ds4: CUDA host registration skipped: operation not supported
ds4: CUDA preparing model tensor mappings
ds4: CUDA loading model tensors into device cache
ds4: CUDA startup model preparation covered 0.99 GiB of tensor spans in 4.062s
ds4: CUDA directly mapped 0.87 GiB auxiliary model
ds4: cuda backend initialized for graph diagnostics
ds4: memory: KV 0.39 GiB (raw 0.34 + compressed 0.05) + buffers 0.03 GiB + resident model 3.36 GiB = 3.78 GiB planned
ds4: memory detail: ctx=4096 prefill_cap=4096 raw_kv_rows=4096 compressed_kv_rows=1026 backend=cuda
ds4: memory: KV 0.39 GiB (raw 0.34 + compressed 0.05) + buffers 0.03 GiB = 0.42 GiB context
ds4: memory detail: ctx=4096 prefill_cap=4096 raw_kv_rows=4096 compressed_kv_rows=1026 backend=cuda
ds4: CUDA loading model tensors 1.86 GiB cached
ds4: CUDA loading model tensors 3.34 GiB cached
ds4: CUDA loading model tensors 4.81 GiB cached
ds4: CUDA loading model tensors 6.28 GiB cached
ds4: CUDA loading model tensors 7.33 GiB cached
ds4: CUDA loading model tensors 7.33 GiB cached
ds4: CUDA loading model tensors 7.33 GiB cached
The user wants me to reply with exactly "LOADGATE OK". This is a simple instruction. I should output that exact phrase.

I'll output "LOADGATE OK".
LOADGATE OK
ds4: prefill: 0.07 t/s, generation: 0.08 t/s
=== RC=0
=== END 11:43:39
               총계         사용        여분      공유    버퍼/캐시    가용
메모리:          121           6         115           0           0         114