Gemma 4 26B-A4B-it + DFlash, FP8 experts โ€” radiance container

google/gemma-4-26B-A4B-it as a single .rad container for the radiance inference engine (AMD RDNA4, ROCm), with z-lab's DFlash block-diffusion drafter merged in for speculative decoding. radiance's Gemma 4 26B-A4B support is by Perire.

File gemma4-26b-a4b-dflash-fp8.rad โ€” 33.94 GiB
Weights the routed experts' gate_up projections FP8 E4M3 per 128ร—128 block (bf16 scales); their down projections, the attention, the dense MLP, the router, the norms and the tied embedding bf16 as the checkpoint ships them
Speculator DFlash, drafting 15 tokens a step. Its linears and its head are FP8 E4M3 per 128ร—128 block; the drafter only proposes, and the model verifies every token it emits
Context 262,144 tokens (the checkpoint's trained length)
Modalities text
Needs radiance 1.5.0 or newer

Serve

radiance --model gemma4-26b-a4b-dflash-fp8.rad --tp 2 --max-model-len 65536 --kv-cache-dtype fp8 \
    --max-num-seqs 8 --max-num-batched-tokens 2048 --draft-window adaptive --host 0.0.0.0 --port 8000

The Docker image is stilldeadcode/radiance. The server speaks the OpenAI API (/v1/chat/completions, /v1/completions), with tool calls and structured output. --draft-window adaptive lets the drafter's window follow how much of it is accepted; without it every step drafts the container's 15 tokens.

Measured on two Radeon AI PRO R9700 (gfx1201), one sequence:

prose code
fixed window (15) 113.7 tok/s 216.7 tok/s
--draft-window adaptive 159.0 tok/s 249.3 tok/s

An 11.5K-token prompt is prefilled in 1.0 s.

How this file was made

rad-convert google/gemma-4-26B-A4B-it --draft-model z-lab/gemma-4-26B-A4B-it-DFlash \
    --recipe gemma4-26b-a4b-df.recipe -o gemma4-26b-a4b-dflash-fp8.rad

The recipe (gemma4-26b-a4b-df.recipe in this repository) names what is quantised; everything it does not name is the checkpoint's bf16:

blk.*.ffn_gate_up_exps.*.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.fc.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.blk.*.attn_q.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.blk.*.attn_k.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.blk.*.attn_v.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.blk.*.attn_output.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.blk.*.ffn_gate_up.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.blk.*.ffn_down.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
dflash.draft_head.weight rtn codes=fp8_e4m3 block=128x128 scale=bf16
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