docs: add DFlash/DSpark speculative decoding research + quantization-by-hardware guide

- 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

docs/index.md

@@ -47,3 +47,8 @@ graph LR
 
 - [[Running Qwen3.6 35B A3B FP8 on Dankserver]] — MoE model (35B total, 3B active) on RTX 3090
 - [[Running Qwen3.6 27B FP8 on Dankclaw]] — Dense model (27B) on Strix Halo APU
+
+## Speculative Decoding & Quantization
+
+- [[DFlash DSpark Speculative Decoding]] — block diffusion (DFlash) and semi-autoregressive (DSpark) drafting on vLLM and llama.cpp
+- [[Quantization by Hardware Architecture]] — which quant format fits which GPU/CPU