ji-farthing/gemma-4-26B-A4B-it-DFlash-SWA-ik-llama-GGUF

Gemma 4 26B-A4B DFlash SWA draft for ik_llama

This repo contains an ik_llama-compatible DFlash draft GGUF converted from z-lab/gemma-4-26B-A4B-it-DFlash, carrying the per-layer sliding-window attention (SWA) pattern.

This is not a standalone chat model. Use it as a --model-draft file next to a matching Gemma 4 26B-A4B IT target GGUF, with DFlash speculative decoding. Gemma 4 needs --jinja.

Sliding-window attention

The draft is sliding-window on every layer except a final full-attention (global) layer: sliding_window_pattern = [true, true, true, true, false], sliding_window = 2048.

Files

Use

llama-server \
  -m /path/to/gemma-4-26B-A4B-it-<quant>.gguf \
  --model-draft /path/to/gemma-4-26B-A4B-it-DFlash-SWA-ik_llama-Q8_0.gguf \
  --spec-type dflash:n_max=4,cross_ctx=8192 \
  -c 8192 --jinja

SWA only engages once the DFlash cross-context exceeds the 2048 window, so set cross_ctx above the window for long-context prompts (the default 512 does not grow with -c).

Validation (RTX 4070, ik_llama DFlash SWA branch)

Draft acceptance and throughput versus the same draft run with full attention, as the prompt overflows the 2048 window, where clip = (prompt - 2048) / prompt:

Conversion

Converted from z-lab/gemma-4-26B-A4B-it-DFlash with ik_llama's convert_hf_to_gguf.py DFlash draft converter (sliding-window support branch), then quantized to Q80. The per-layer SWA pattern is taken from the source `layertypes. Conversion requires a --target-model-dir` containing the target tokenizer merges.