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# I tried Google's new DiffusionGemma, and watching it generate text like an image is unlike any local LLM

**[XDA Developers](https://daily.dev/sources/xda-developers)** · 9 min read · 0 upvotes · 0 comments

## Summary

Google's DiffusionGemma is an experimental open model that generates text using a diffusion process rather than left-to-right autoregressive token generation. Instead of streaming tokens one at a time, it works on a 256-token canvas, repeatedly refining placeholder text until the answer coalesces — visually similar to watching an image generator denoise. Running it locally requires a custom llama.cpp fork and a dedicated llama-diffusion-cli runner via Unsloth's GGUF path. On an M4 Pro MacBook Pro, it was slower than regular Gemma 4 and caused system-wide slowdowns, as Google's speed claims (up to 4x faster, 700+ tokens/sec) apply to dedicated Nvidia GPUs, not Apple Silicon. Quality-wise, Google acknowledges it trails standard Gemma 4 across benchmarks. The model's appeal is conceptual: bidirectional attention within a block canvas enables inline editing, code infilling, and non-linear text structures that left-to-right generation handles less naturally.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.xda-developers.com/tried-google-diffusiongemma-generate-text-like-image-local-llm>

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---

Tags: [#local-ai](https://daily.dev/tags/local-ai), [#text-generation](https://daily.dev/tags/text-generation), [#gemma](https://daily.dev/tags/gemma), [#llama-cpp](https://daily.dev/tags/llama-cpp)

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