this post was submitted on 01 Jul 2025
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Microblog Memes
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A place to share screenshots of Microblog posts, whether from Mastodon, tumblr, ~~Twitter~~ X, KBin, Threads or elsewhere.
Created as an evolution of White People Twitter and other tweet-capture subreddits.
RULES:
- Your post must be a screen capture of a microblog-type post that includes the UI of the site it came from, preferably also including the avatar and username of the original poster. Including relevant comments made to the original post is encouraged.
- Your post, included comments, or your title/comment should include some kind of commentary or remark on the subject of the screen capture. Your title must include at least one word relevant to your post.
- You are encouraged to provide a link back to the source of your screen capture in the body of your post.
- Current politics and news are allowed, but discouraged. There MUST be some kind of human commentary/reaction included (either by the original poster or you). Just news articles or headlines will be deleted.
- Doctored posts/images and AI are allowed, but discouraged. You MUST indicate this in your post (even if you didn't originally know). If a post is found to be fabricated or edited in any way and it is not properly labeled, it will be deleted.
- Be nice. Take political debates to the appropriate communities. Take personal disagreements to private messages.
- No advertising, brand promotion, or guerrilla marketing.
Related communities:
founded 2 years ago
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Not at all. Not even close.
Image generation is usually batched and takes seconds, so 700W (a single H100 SXM) for a few seconds for a batch of a few images to multiple users. Maybe more for the absolute biggest (but SFW, no porn) models.
LLM generation takes more VRAM, but is MUCH more compute-light. Typically one has banks of 8 GPUs in multiple servers serving many, many users at once. Even my lowly RTX 3090 can serve 8+ users in parallel with TabbyAPI (and modestly sized model) before becoming more compute bound.
So in a nutshell, imagegen (on an 80GB H100) is probably more like 1/4-1/8 of a video game at once (not 8 at once), and only for a few seconds.
Text generation is similarly efficient, if not more. Responses take longer (many seconds, except on special hardware like Cerebras CS-2s), but it parallelized over dozens of users per GPU.
This is excluding more specialized hardware like Google's TPUs, Huawei NPUs, Cerebras CS-2s and so on. These are clocked far more efficiently than Nvidia/AMD GPUs.
...The worst are probably video generation models. These are extremely compute intense and take a long time (at the moment), so you are burning like a few minutes of gaming time per output.
ollama/sd-web-ui are terrible analogs for all this because they are single user, and relatively unoptimized.