Frank
6efb0fb231
Replace the llama.cpp Tiel-Coder-35B-A3B (UD-Q6_K_XL) deployment with FreeToken v0.1.2 — an edge-native MoE serving engine that keeps expert weights in host RAM with an LRU GPU cache and paged KV with radix prefix sharing. Model: Qwen/Qwen3.6-35B-A3B-FP8 (modelopt block-fp8, 128×128 weight_block_size). Architecture: qwen3_5_moe — 40 layers (10 attention + 30 GDN), 256 experts/8 used. Production config: - 2048 MoE cache slots (20% of 10240 expert instances, ~6.0 GiB VRAM) - 453005 KV tokens (~8.6 GiB, ~20 KiB/token for 10 attn layers) - 4 max-running-requests (mamba slot pool: 24 slots) - bs4 decode: ~87 tok/s aggregate, ~30 tok/s bs1 - Prefill: ~1,130 tok/s at 4k prompt Quirk: FreeToken v0.1.2 supports modelopt block-fp8, NVFP4, and per-tensor FP8, but NOT compressed-tensors per-channel FP8 (Huihui/Ornith both failed). Live KV resize via ft ctl cache grows KV by shrinking MoE; reverse needs restart. Old llama.cpp scripts archived to .AGENTTRASH/. Full benchmark sweep (bs1/bs3/bs4/bs6, 8k–700k KV) documented in docs/LLM/freetoken-benchmark-sweep.md.
87 lines
2.7 KiB
C++
Executable File
87 lines
2.7 KiB
C++
Executable File
#!/usr/bin/env bash
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# Serve peculiar-ragdoll/Tiel-Coder-35B-A3B (UD-Q6_K_XL) as
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# frank-default-small via stock llama.cpp on Dankserver (RTX 3090).
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#
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# Runtime: upstream llama.cpp (latest master, CUDA build with
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# -DGGML_CUDA_FA_ALL_QUANTS=ON -DCMAKE_CUDA_ARCHITECTURES=86).
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# The model is a 35B-total / 8-active MoE hybrid (qwen35moe arch) with
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# SSM/Mamba layers (full_attention_interval=4: 10 attention + 30 SSM
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# layers out of 40). 256 experts, 8 used per token.
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#
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# Expert offload: --cpu-moe keeps all 256 expert weights in CPU RAM.
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# Non-expert weights (attention, SSM, shared expert, embeddings, output)
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# are ~1.6 GB and fit entirely on the 24 GB RTX 3090.
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#
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# KV cache: Q8_0 for both K and V. With CTX_SIZE=200700 (66 900 per
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# slot × 3 parallel) and 10 attention layers (2 KV heads × 256 dim),
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# the KV cache is ~2 GB — the requested 2 GB VRAM buffer.
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#
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# Model is loaded with mmap (default). The 30 GB Q6_K_XL file is
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# memory-mapped; only accessed pages enter RAM.
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#
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# Tunables come from frank-default-small.env unless FRANK_SMALL_ENV_FILE
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# overrides that path.
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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ENV_FILE="${FRANK_SMALL_ENV_FILE:-$SCRIPT_DIR/frank-default-small.env}"
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if [[ -f "$ENV_FILE" ]]; then
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set -a
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# shellcheck disable=SC1090
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source "$ENV_FILE"
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set +a
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fi
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# --- defaults (used when the env file does not set them) -----------------
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: "${MODEL_DIR:=/home/dank/models/tiel-coder-35b}"
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: "${MODEL_FILE:=Tiel-Coder-35B-A3B-UD-Q6_K_XL.gguf}"
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: "${LLAMA_SERVER:=/home/dank/llama.cpp/build/bin/llama-server}"
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: "${ALIAS:=frank-default-small}"
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: "${BIND_ADDR:=0.0.0.0}"
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: "${LISTEN_PORT:=7770}"
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: "${CTX_SIZE:=200700}"
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: "${PARALLEL:=3}"
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: "${CACHE_TYPE_K:=q8_0}"
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: "${CACHE_TYPE_V:=q8_0}"
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: "${N_GPU_LAYERS:=999}"
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: "${BATCH_SIZE:=4096}"
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: "${UBATCH_SIZE:=1024}"
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: "${VERBOSITY:=2}"
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: "${CPU_MOE:=1}"
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: "${TEMPERATURE:=1.0}"
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: "${TOP_K:=20}"
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: "${TOP_P:=0.95}"
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: "${MIN_P:=0.0}"
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: "${THREADS:=7}"
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: "${THREADS_HTTP:=8}"
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MODEL="$MODEL_DIR/$MODEL_FILE"
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if [[ ! -f "$MODEL" ]]; then
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echo "missing required file: $MODEL" >&2
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exit 1
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fi
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if [[ ! -x "$LLAMA_SERVER" ]]; then
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echo "missing llama-server binary: $LLAMA_SERVER" >&2
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exit 1
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fi
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exec "$LLAMA_SERVER" \
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--model "$MODEL" \
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$([ "$CPU_MOE" = "1" ] && printf -- "--cpu-moe") \
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--cache-type-k "$CACHE_TYPE_K" \
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--cache-type-v "$CACHE_TYPE_V" \
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--ctx-size "$CTX_SIZE" \
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--parallel "$PARALLEL" \
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--gpu-layers "$N_GPU_LAYERS" \
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--batch-size "$BATCH_SIZE" \
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--ubatch-size "$UBATCH_SIZE" \
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--temp "$TEMPERATURE" \
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--top-k "$TOP_K" \
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--top-p "$TOP_P" \
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--min-p "$MIN_P" \
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--threads "$THREADS" \
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--threads-http "$THREADS_HTTP" \
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--alias "$ALIAS" \
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--host "$BIND_ADDR" \
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--port "$LISTEN_PORT" |