 Frank
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6efb0fb231
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feat: replace llama.cpp Tiel-Coder with FreeToken v0.1.2 serving Qwen3.6-35B-A3B-FP8
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.
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2026-08-27 02:01:16 -07:00 |
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