@rohanpaul_ai: atomic[.]chat shared a revealing comparison of local open-weight LLMs running on their own hardware. They benchmarked t…

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Summary

A benchmark comparison of local open-weight LLMs on a single H100 (FP8) shows DiffusionGemma is 4x faster but makes 6x more mistakes than Gemma4 26B A4B, highlighting trade-offs between speed and accuracy in diffusion versus autoregressive models.

atomic[.]chat shared a revealing comparison of local open-weight LLMs running on their own hardware. They benchmarked the new DiffusionGemma (diffusion text model) vs. Gemma4 26B A4B (autoregressive model) on a single H100 (FP8). The 4X speed of DiffusionGemma changes the shape of error. - Autoregressive models move left to right, one token at a time, which is slower, but each new word is conditioned on the exact text already written. - Diffusion models write many tokens at once, then revise the block over several passes, so they can feel fast because the model is not waiting to finish token 1 before starting token 2. atomic[.]chat, a desktop app for running LLMs locally
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Cached at: 06/12/26, 02:50 AM

atomic[.]chat shared a revealing comparison of local open-weight LLMs running on their own hardware.

They benchmarked the new DiffusionGemma (diffusion text model) vs. Gemma4 26B A4B (autoregressive model) on a single H100 (FP8).

The 4X speed of DiffusionGemma changes the shape of error.

  • Autoregressive models move left to right, one token at a time, which is slower, but each new word is conditioned on the exact text already written.

  • Diffusion models write many tokens at once, then revise the block over several passes, so they can feel fast because the model is not waiting to finish token 1 before starting token 2.

atomic[.]chat, a desktop app for running LLMs locally

atomic.chat (@atomic_chat_hq): Diffusion Gemma is 4x faster, but makes 6x more mistakes!

We benchmarked the new diffusion LLM against its autoregressive twin on a single H100 (FP8). We gave each the same three tasks: write a Steve Jobs biography, the history of Tetris, and the story of BeOS - every next topic

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