Replaces llama.cpp Gemma4-12B-QAT (payload + binary retained as rollback). SGLang in a self-contained python3.12 venv with an extracted CUDA 13.0 nvcc toolchain for the sgl-kernel/flashinfer JIT. Shape: fp8 KV, pinned 606,208-token pool / 4 x 151,552 slots, bf16 mamba states pinned at 32 slots (the engine autofills the ssm pool to a fixed ~5.1 GB regardless of dtype), eager prefill (no headroom for graph capture), no spec decode (the checkpoint ships no mtp.* tensors despite mtp_num_hidden_layers=1 — NEXTN drafts with an uninitialised 4.24 GiB ghost at 0% acceptance). Verified: 83.9 tok/s decode, 170k single prompt, 4 concurrent 54k requests, vision (in-checkpoint tower), reasoning_content field.
20 lines
603 B
Desktop File
20 lines
603 B
Desktop File
[Unit]
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Description=SGLang MiMo-V2.6-Distill-Qwen-9B-INT8 (qwen3_5 hybrid, MTP+vision) 4x172k fp8 KV (dankclaw, frank-small)
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After=network-online.target
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Wants=network-online.target
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[Service]
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Type=simple
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User=dank
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Group=dank
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# CUDA pins its staging buffers, so the process needs the memlock budget even
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# though the weights themselves are copied into VRAM.
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LimitMEMLOCK=infinity
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Environment="FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-small.env"
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ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-small.sh
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Restart=on-failure
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RestartSec=10
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[Install]
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WantedBy=multi-user.target
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