🤯 This is like having Jev at home, a AI reflex system running locally. Someone is turning Google's open DiffusionGemma 26B-A4B into a local version of the new “System One” AI idea inside vLLM. Remember Jev? It is a decision LLM. Instead of asking an LLM to generate paragraphs, System One models are designed to make FAST structured decisions: 🎯 yes / no 🧭 route A / B / C 🛠️ which tool to call 🚨 severity 1–4 📊 classify / score / choose And DiffusionGemma has an important role because a normal autoregressive LLM takes Prompt ↓ token ↓ answer DiffusionGemma is Prompt ↓ predefined answer slots ↓ fill multiple decisions in parallel Because it operates over a token canvas with bidirectional attention instead of being forced to generate everything strictly left-to-right. The vLLM patch lets it return ✅ bounded choices ✅ probabilities ✅ confidence / uncertainty ✅ multiple decisions simultaneously And it runs locally. On ONE DGX Spark the developer reports ⚡ 1 request: ~120 ms 🚀 concurrency 32: ~54 requests/sec 🧠 3 decisions/request 🔥 ~162 decisions/sec Then the developer found each question can require only around 3 canvas tokens: 🔢 index ❓ placeholder ✂️ separator Meaning as many as ~85 questions could fit into 1 diffusion canvas. And subsequent optimization reportedly cut decision time another: ⚡ ~20–40% with no change in decision quality. The model stats ... 🧠 25.2B total parameters ⚡ 3.8B active 💾 NVIDIA NVFP4: ~18.9GB 🎮 Can fit on a 24GB NVIDIA GPU 📜 Open weights ⚠️ vLLM PR #57250# is still OPEN 👉 not merged. And this is Jev-like functionality. It is NOT evidence that DiffusionGemma matches Jev's intelligence or calibration. 🔗 /vllm-project/vllm/pull/57250