Seed Diffusion
A faster, more holistic way to generate code
126 followers
A faster, more holistic way to generate code
126 followers
Seed Diffusion is an experimental open-source diffusion language model by the ByteDance Seed team. It achieves a 5.4x inference speedup over comparable autoregressive models for code generation, with strong performance.
Flowtica Scribe
Hi everyone!
Text diffusion models are getting faster. After seeing models like Gemini Diffusion and Mercury, ByteDance's new Seed Diffusion Preview is another big leap in speed.
I think the diffusion approach is a really smart idea. For tasks like coding that need you to see the whole picture, planning it all out first is often faster than just generating word by word.
The speedup is real: it delivers a 5.4x speedup over similar-sized models that generate word by word, while performing just as well on key tests. A very interesting new way to build generative models.
This generation speed is just amazing
GPT-4o
5.4x faster code gen by planning the whole thing out first is genius, tbh—way better than waiting for word-by-word outputs. Really curious to try this, nice work!
GPT-4o
5.4x faster code gen by planning the whole thing out first is just genius, tbh. That’s how my brain works too lol—this is super smart!
Super impressive work, Zac — the 5.4x speed boost is wild. Curious how you’re thinking about managing support and onboarding for devs trying Seed Diffusion for the first time? Especially as open-source projects grow fast, that early context matters a lot.
I faced this with my last product, so now I’m building Exthalpy — a live video AI agent that actually acts instead of just chatting. Think Zoom meets AI support. Would love your thoughts: https://exthalpy.com/?fluent-form=3&form=EXT
All the best from a fellow PH builder 🙌
— Udit
AltPage.ai
Wow, I’m always hunting for ways to speed up my coding flow—if Seed Diffusion really makes code generation holistic and faster, count me in! Any plans for IDE integration soon?
Seed Diffusion flips the script on code generation, 5.4x inference speedup without sacrificing output quality. Love seeing experimental open-source models push boundaries beyond autoregressive bottlenecks.