DiffusionGemma as Jev: single-pass parallel denoising decisions in ~0.2s on DGX Spark
bodonoghue85 · x · 2026-09-20
Google's Gemma account highlighted "DiffusionGemma as Jev," a demo app showcasing non-autoregressive architectures for rapid decision-making.
- Massive parallelism: canvas diffusion denoises across an open canvas in a single step instead of sequential autoregressive generation, evaluating all structured choices in one parallel pass (0.2s on a DGX Spark).
- Full bidirectional attention: every option attends to the full context concurrently, yielding well-calibrated decision distributions.
- Multimodal grounding: inherits Gemma 4's spatial vision for complex visual and text decisions.
Several developers report it runs even faster than the original Jev on some tasks, marking a practical use of diffusion LMs in the rapid-decision paradigm.
Related event: Google's DiffusionGemma Makes Decisions in 0.2s via Parallel Denoising(2 posts)→
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