r/LocalLLM: rules, karma requirements and posting culture
A busy, loosely moderated room for running language models at home. Hardware questions, rig photos and weekend projects, with more patience for beginners than most AI subreddits.
LocalLLM · Open on Reddit
- Members
- 237k
- Created
- 2023
- New posts a day
- 136.5
- Comments on a typical post
- 4
- New posts removed
- 16%
The short answer
r/LocalLLM publishes no karma or account age requirement, and there are no AutoModerator messages in our sample to suggest a hidden one. About 84% of new posts stayed up. The rest were caught by Reddit's own filters, and we saw no moderator removals at all. Every post carries a flair, and Question is the biggest at about 40%. Expect a few replies, not a crowd: the median post gets three or four comments.
Who posts here
The same feed holds a self-described noob asking whether a local model can summarise a video in 16 GB of memory and someone extending an inference engine fork from two GPUs to four. Basic questions stay up and get answered, and one of the top recent posts simply asked what an uncensored model is. The rules do call install and where-to-find-models questions low effort, so a question with no specifics is the one that gets ignored.
- Newcomers choosing a first GPU, mini PC or Mac for local models and asking what will fit.
- Hobbyists with multi-GPU rigs who post photos of the build and the bill.
- Developers trying to replace a paid coding assistant with a model on their own machine.
- Tinkerers shipping engines, forks, benchmarks and small models under the Project flair.
- People who care about privacy and want their data off other companies' servers.
Karma and account requirements
What it takes to get a post through in r/LocalLLM.
| Karma | Not stated publicly. No rule or AutoModerator message in our sample mentions a threshold. |
|---|---|
| Account age | Not stated publicly. |
| Post flair | Every post in our sample has one. Question is about 40%, Discussion 23% and Project 20%, with News, Model, Research and Tutorial making up the rest. |
| Topic | Local models first, but the rule is written to allow language models in general.Mods' wording: “Posts must be directly related to locally run LLMs or the topic of LLMs.” |
| Self-promotion ratio | The one in ten guideline: no more than 10% of what you post here should be your own thing.Mods' wording: “self-promotion should not be more than 10% of your content here” |
| Project links | Link directly to the source. No affiliate links and no sensational titles, for your own project or someone else's.Mods' wording: “Links must be directly to the source, such as GitHub or Hugging Face.” |
What you can post
| Post type | Subreddit setting | Share of recent posts |
|---|---|---|
| Text | Allowed | 57% |
| Link | Allowed | 28% |
| Image | Allowed | 11% |
| Video | Allowed | 3% |
| Poll | Allowed | <1% |
Post flairs in use
- Question 41%
- Discussion 23%
- Project 20%
- News 5%
- Model 5%
- Research 4%
- Tutorial 2%
- Other 1%
- Contest Entry <1%
What happens to a new post
Where the most recent posts ended up. Sample size: 400.
- Stayed up84%
- Removed by Reddit's filters16%
- Deleted by the author<1%
Reddit counts a removal by the subreddit's own AutoModerator rules as a moderator removal, so that share is not all human. Held by AutoModerator means the post is waiting in the mod queue.
What happened when we posted here
We have posted here ourselves. This is how our own posts and comments fared.
- Stayed up
- 100%
- Removed by Reddit's filters
- 0%
- Removed by moderators
- 0%
- Period
- January 2026 to August 2026
The rules, in the mods' words
- 1
Off-Topic Posts
Posts must be directly related to locally run LLMs or the topic of LLMs.
- 2
Low Effort Posts
This mainly includes questions that are very simple and can be answered with basic research, like "How do I install this?" or "Where can I find models?" If you're receiving errors when running something, the first place to search is the issues page for the repository of the project you're using.
- 3
Limit Self-Promotion
This is an open community that highly encourages collaborative resource sharing, but the sub is not here as merely a source for free advertisement. The 1/10th rule is a good guideline: self-promotion should not be more than 10% of your content here. Additionally, if you are sharing your or someone else's project, please do not use any sensationalized titles, and do not use any affiliate links when linking to content. Links must be directly to the source, such as GitHub or Hugging Face.
- 4
Follow Reddit's Content Policy
Posters and commenters are expected to act in good faith. Treat other users the way you want to be treated. Avoid straw-manning and bad-faith interpretations. Avoid presenting misinformation as factual. Please remember to follow Reddit's Content Policy (https://www.redditinc.com/policies/content-policy).
These are the rules as archived in February 2025. Rules change. Check the sidebar before you post.
The culture
r/LocalLLM has about 237,000 members and a lot of traffic, well over 100 posts a day. It is the less formal of the local model subreddits. The feed is mostly people working out what to buy and what to run on it: which quant fits a 16 GB card, two used GPUs against four new ones, a Mac against a workstation card.
Text posts are about 57% of the total and links about 28%, many of them crossposts. The posts that rise are easy to like: a photo of a new rig, a hard-to-find card finally arriving, a kid building a chatbot on the family server, a month of running one model for real work with the numbers attached. News that a new open-weight model is confirmed tops the recent list.
The argument running through the comments is about trust. A new inference engine has had a wave of enthusiastic posts, and some readers now assume the people posting results are bots or paid. Others push back and ask for criticism that says something. If you post numbers, expect to be asked how you got them.
What lands
- Build posts with a photo, a parts list and what it cost. Several of the top recent posts are exactly this.
- Long-run reports: a model used daily for weeks, with speeds, failures and what it replaced.
- A hardware choice laid out as two concrete options, with budget and use case stated.
- Benchmarks on cheap or odd hardware, such as a budget phone or old data centre cards.
- Posts about leaving a paid AI service for a local model, usually for privacy or cost.
What gets removed or ignored
- We saw no moderator removals in our sample, so there is no pattern to report from the mods. About 16% of posts were removed by Reddit's own filters, and our data does not show why.
- By rule, questions basic research would answer: how to install something, where to find models.
- By rule, error reports that belong on the project's own issues page.
- By rule, sensational titles and affiliate links on shared projects.
The unwritten rules
- List your hardware in the post. CPU, GPU and VRAM, system RAM, operating system. Answers depend on all of it.
- Do not expect volume. The median post gets three or four comments, so judge a question by whether one good answer arrives.
- Link posts with nothing in the body are common here and mostly sink. A few lines on what you tested does better.
- Links in comments are normal, about one in ten carries one, and they point at repos and model pages.
- Breathless posts about one tool draw bot and shill accusations. Give your setup, your method and at least one thing that went wrong.
Self-promotion
The rule says the subreddit encourages sharing but is not a source of free advertising, and sets the one in ten guideline: self-promotion should be no more than 10% of your content here. Projects must link straight to the source, with no affiliate links and no sensational titles. In practice enforcement looks light. The Project flair is about a fifth of all posts, people share engines, apps and models they made, and our sample shows no moderator removals. The check comes from the comments, where anything that reads like a campaign gets called out.
How people write here
- Typical post length
- 127 words
- Typical title length
- 12 words
- Titles phrased as a question
- 31%
- Typical comment length
- 23 words
- Comments that include a link
- 10%
- Posts that carry a flair
- 100%
Top keywords
The words and phrases that show up far more often here than in other communities, from recent posts in r/LocalLLM.
- model 141 posts
- local 126 posts
- models 107 posts
- qwen 64 posts
- ram 64 posts
- gpu 53 posts
- llm 75 posts
- rtx 41 posts
- vram 40 posts
- local llm 34 posts
- tokens 49 posts
- coding 57 posts
- gb ram 32 posts
- hardware 44 posts
- inference 37 posts
- memory 52 posts
- tok 29 posts
- context 61 posts
- llms 38 posts
- flash 30 posts
- strata 25 posts
- local ai 22 posts
- mac 30 posts
- prefill 22 posts
- llama.cpp 25 posts
- cpu 27 posts
- pro 39 posts
- local models 23 posts
- ryzen 19 posts
- locally 31 posts
- local llms 19 posts
- setup 50 posts
- speed 33 posts
- decode 20 posts
- qwen3.8 19 posts
- qwen3.8-flash-next 17 posts
- gb vram 18 posts
- mac studio 13 posts
- hermes 19 posts
- rtx gb 15 posts
Common questions
How much karma do you need to post in r/LocalLLM?
No karma or account age requirement is published, and we found no AutoModerator message that mentions one. About 16% of posts in our sample were removed by Reddit's own filters, which the subreddit does not control or explain, so a very new account may still have trouble.
Can I promote my project in r/LocalLLM?
Yes, in moderation. The rules say self-promotion should be no more than 10% of your content here, that links must go directly to the source such as GitHub or Hugging Face, and that titles must not be sensational. Use the Project flair and include real numbers from your own hardware.
What is the difference between r/LocalLLM and r/LocalLLaMA?
They cover the same subject. r/LocalLLM is the smaller one, at about 237,000 members, and it leans more toward questions: Question is its largest flair at about 40% of posts. Its rules are short, and in our sample no posts were removed by moderators.
What kind of posts work in r/LocalLLM?
Hardware build posts with photos, reports from running a model for real work, and specific buying questions. The typical post is about 127 words and around a third of titles are questions. State your hardware and what you want to do with it.
Data as of October 4, 2026. Numbers come from public Reddit data (the Arctic Shift archive and GummySearch) sampled on this date. Removal share counts posts taken down by moderators, AutoModerator or Reddit's own filters. Banner and icon belong to the community. Moderators change rules without notice, so treat the sidebar as the final word.
