Total KV: ~12.8 GiB (6.4 GiB per slot × 2). Model is 98.5 GiB mmap'd into 116 GiB SVM-backed unified memory.
81 lines
3.3 KiB
Bash
81 lines
3.3 KiB
Bash
# Tunables for frank-default-large (kingjones777 Qwen3.8-Flash-Next
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# ROCmFP4 STRIX_LEAN, qwen4exp hybrid MoE, Dankclaw, Strix Halo gfx1151).
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#
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# Runtime: ROCmFPX llama.cpp fork with PR #27742 (qwen4exp architecture)
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# merged and built at /home/dank/GitPackages/ROCmFPX/build-qwen38.
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# Build flags: -DGGML_HIP=ON -DGGML_HIP_ROCMI4_W4A4=ON
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# -DCMAKE_HIP_ARCHITECTURES=gfx1151 -DGGML_CUDA_FA_ALL_QUANTS=ON
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# -DLLAMA_BUILD_WEBUI=OFF -DCMAKE_EXE_LINKER_FLAGS=-no-pie.
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# Replaced the kingjones Qwen3.8-27B Q6_0 AGENT deployment on 2026-09-01.
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#
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# Model: kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN-GGUF.
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# 56B MoE (512 experts, 10 used), 48 layers (12 attention + 36 SSM,
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# full_attention_interval=4), 2 KV heads × 256 dim, embedding 2560,
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# QSA indexer (4 heads, key_length 128, top_k 2048), hyper-connections
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# (count=4, low_rank=320), PLE (layer 1, ngram_size=3, heads_per_ngram=8).
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# Q4_0_ROCMFP4_STRIX_LEAN quant, 98.5 GiB, 3-part GGUF split.
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# Text-only (no mmproj, no MTP draft head).
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#
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# Context: 262144 (256k) × 2 slots. f16 KV cache (~6.4 GiB per slot,
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# ~12.8 GiB total). --fit off because the auto-fit code segfaults on this
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# model's hyper-connection/indexer config; -ngl 999 places all layers on
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# the SVM-backed GPU pool (116 GiB unified).
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#
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# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE. The
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# ROCm HIP runtime reads those bare env vars (see the 2026-08-13 TEMP
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# incident). llama.cpp reads --host/--port/--temp as CLI flags, never as
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# env vars.
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# ROCmFPX llama-server (PR #27742 merged, build-qwen38).
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LLAMA_BIN=/home/dank/GitPackages/ROCmFPX/build-qwen38/bin/llama-server
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# Model files from
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# https://huggingface.co/kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN-GGUF
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MODEL_DIR=/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN
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MODEL_FILE=Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN-00001-of-00003.gguf
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# Qwen-Sharp chat template (tracked in the repo, staged on the host). The
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# Sharp template drives thinking on by default (medium effort); the server
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# emits reasoning in DeepSeek format so clients receive reasoning_content
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# separately instead of literal thinking tags in content.
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CHAT_TEMPLATE_FILE=/home/dank/serverAppConfigs/scripts/chat-template.jinja
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CHAT_TEMPLATE_KWARGS='{"enable_thinking":true,"preserve_thinking":true,"preserve_reasoning":true}'
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# Alias + network.
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ALIAS=frank-default-large
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BIND_ADDR=0.0.0.0
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LISTEN_PORT=7770
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# Serving: 262144 context (256k) × 2 slots. f16 KV, context checkpoints,
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# prompt cache. The model is 98.5 GiB loaded via mmap into the Strix Halo
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# unified memory pool (116 GiB SVM-backed). --fit off avoids the auto-fit
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# segfault on this model's qwen4exp hyper-connection/indexer configuration.
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CTX_SIZE=524288
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PARALLEL=2
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BATCH_SIZE=4096
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UBATCH_SIZE=4096
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NUM_THREADS=16
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THREAD_BATCH=32
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CACHE_TYPE_K=f16
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CACHE_TYPE_V=f16
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CTX_CHECKPOINTS=16
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CACHE_RAM=8192
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FIT=off
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# Sampling (Sharp default).
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TEMPERATURE=0.7
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TOP_K=20
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TOP_P=0.8
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MIN_P=0.0
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PRESENCE_PENALTY=1.5
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# Reasoning on (Sharp template drives it; preserve_thinking + preserve_reasoning
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# keep the reasoning trail in the conversation). DeepSeek format projects the
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# reasoning into the API's reasoning_content field instead of content tags.
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REASONING=on
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REASONING_FORMAT=deepseek
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# Strix Halo unified memory + native gfx1151.
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HSA_OVERRIDE_GFX_VERSION=11.5.1
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VERBOSITY=4 |