993b6af57607fbca1ce3ceb307d20e5d10c11b1e
- DFlash DSpark Speculative Decoding.md: verified method details (DFlash block diffusion from Z Lab arXiv:2602.06036; DSpark semi-autoregressive from DeepSeek arXiv:2607.05147), runtime support matrix (vLLM/llama.cpp/SGLang), exact vLLM --speculative-config recipes (incl. dflash/dspark), llama.cpp --spec-type recipes with sidecar auto-discovery, draft model table (z-lab Qwen3.6-27B-DFlash 2B, Qwen3.6-35B-A3B-DFlash 0.4B), deployment guidance for RTX 3090 (AWQ+Dflash) and Strix Halo (ROCmFPX MTP), measured 45-50 t/s MTP decode on Strix Halo - Quantization by Hardware Architecture.md: FP8/INT8/INT4/GPTQ/AWQ/GGUF/FP4/ ROCmFP4 support per NVIDIA (Turing/Ampere/Ada/Hopper/Blackwell), AMD (CDNA MI250/MI300/MI350, RDNA 3/3.5/4), and CPU; recommended picks per Dankserver (AWQ/GPTQ 4-bit) and Dankclaw (ROCmFP4/Q4_K_M) - index.md: link both new pages under Speculative Decoding & Quantization
vLLM Scripts
Scripts for running large language models via vLLM on two local machines.
Targets
| Host | User | Codename | Architecture |
|---|---|---|---|
| dankserver | dank | DankServer | NVIDIA GPU + System RAM |
| dankclaw | dank | DankClaw | AMD Strix Halo (Shared Memory) |
Models
| Model | Target | Format |
|---|---|---|
| Qwen3.6 35B A3B FP8 | dankserver | FP8 |
| Qwen3.6 27B FP8 | dankclaw | FP8 |
Structure
docs/— Project knowledge base with research notes on vLLM configuration, hardware specifics, and deployment notesscripts/— Executable vLLM launch scripts (coming soon)
Knowledge Base
See docs/README.md for the project knowledge base index.
Languages
Shell
60.4%
Python
21%
HTML
6.2%
Jinja
3.9%
C++
3.9%
Other
4.6%