docs: DiffusionGemma research + first-hand smoke test on 3090 Ti

google/diffusiongemma-26B-A4B-it (released 2026-06-10) — Google's first
open-weight text-diffusion LLM. Does NOT run in Ollama (unknown arch
'diffusion-gemma'); built llama-diffusion-cli from ggml-org/llama.cpp PR
#24423 and smoke-tested Q4_K_M on steel141's 3090 Ti.

- New reference doc with specs, build recipe, throughput, and gotchas
- CORPUS_ollama_variants.md: "not an Ollama variant" callout
- README index line for the reference doc
- scripts/diffusiongemma-smoketest/ harness + raw result logs

Findings: ~106 tok/s effective / ~2030 tok/s in-step-parallel; correct code
+ coherent reasoning; <|channel>thought CoT eats the 256-tok canvas so strict
short formats need block budgeting. nvidia-smi index != CUDA index on steel141
(select 3090 Ti by UUID). Experimental research artifact, not homelab-deployable
until diffusion arch merges to llama.cpp mainline.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

scripts/diffusiongemma-smoketest/run.sh

@@ -0,0 +1,46 @@
+#!/usr/bin/env bash
+# DiffusionGemma smoke test — steel141 3090 Ti
+#
+# DiffusionGemma (google/diffusiongemma-26B-A4B-it, released 2026-06-10) is a
+# text-DIFFUSION MoE model. It does NOT run in Ollama or stock llama.cpp:
+# the standard llama-cli/llama-server reject arch 'diffusion-gemma'. It needs
+# the dedicated `llama-diffusion-cli` binary from ggml-org/llama.cpp PR #24423
+# (danielhanchen / Unsloth), which denoises 256-token canvas blocks in parallel.
+#
+# This harness runs a few non-interactive prompts and captures wall-clock + the
+# diffusion step/block telemetry the CLI prints.
+set -euo pipefail
+
+CLI="${CLI:-/mnt/ai_data/diffusiongemma/llama.cpp/build/bin/llama-diffusion-cli}"
+MODEL="${MODEL:-/mnt/ai_data/diffusiongemma/gguf/diffusiongemma-26B-A4B-it-Q4_K_M.gguf}"
+NGL="${NGL:-99}"          # offload all layers to GPU
+NPRED="${NPRED:-256}"     # one full canvas
+OUTDIR="${OUTDIR:-$(dirname "$0")/results}"
+mkdir -p "$OUTDIR"
+
+[ -x "$CLI" ]   || { echo "missing CLI: $CLI" >&2; exit 1; }
+[ -f "$MODEL" ] || { echo "missing model: $MODEL" >&2; exit 1; }
+
+run() {
+  local name="$1"; local prompt="$2"; shift 2
+  local log="$OUTDIR/${name}.log"
+  echo "=== $name ===" | tee "$log"
+  echo "prompt: $prompt" | tee -a "$log"
+  local t0 t1
+  t0=$(date +%s.%N)
+  "$CLI" -m "$MODEL" -ngl "$NGL" -n "$NPRED" --diffusion-eb auto -p "$prompt" "$@" 2>&1 | tee -a "$log"
+  t1=$(date +%s.%N)
+  echo "WALL_SECONDS=$(echo "$t1 - $t0" | bc)" | tee -a "$log"
+  echo | tee -a "$log"
+}
+
+# 1) Plain reasoning — sanity + coherence
+run reasoning "Explain in three sentences why diffusion language models can be faster than autoregressive ones."
+
+# 2) Code — structured output the diffusion canvas has to fill coherently
+run code "Write a Python function is_prime(n) with a docstring. Output only the code."
+
+# 3) Instruction following with a hard format constraint
+run format "List exactly five primary colors of light, one per line, no extra text."
+
+echo "All runs complete. Logs in $OUTDIR"