That would be such a good title! Why didn’t I think of that? 😅

The woman’s modelling career.

WDYM? The joke about Chinese models (like Qwen, DeepSeek, etc.) won’t work without this.

Yeah, 27B only usable if you can fit it entirely in VRAM. Only MoE models are fine to split, like the mentioned Qwen 3.8 Flash Next. Even though it’s large, only the active 6B parameters needs to be located in VRAM, the rest can be in RAM and SSD.

Nice to hear!

Please, ping me once you get the approval, I prefer F-Droid over Obtainium 🙂

It’s is expected, they’re small models. But something like Qwen 3.8 27B or Qwen 3.8 Flash Next should handle it.

How much VRAM do you have? If it’s a 12GB card and you also happens to have 64 GB of RAM, you should be able to run Qwen 3.8 Flash Next with Q3. It’s one of the most “hyped” local models right now (because it’s quite capable and has somewhat realistic HW requirements).

That’s insane. I bought mine last month for ~900$.

Oh yeah! But I think something like Qwen 3.8 27B should be able to handle it 🤔

We’re in !ocalllama@sh.itjust.works. So if this goes to the service you own (runs on your PC, for example) - I think it’s fine. The author confirmed the local models are supported.

If the model is local and since the APP is FOSS, it’s probably fine.

Local models already work: in Settings you can add a custom OpenAI-compatible address (llama.cpp, Ollama or LM Studio on your network)

You should’ve mentioned this in the readme 🙂 I’ll check it out!

deleted by creator

I didn’t know it has ads. I used it to avoid sending a direct link to Twitter.

I assume it’s to simplify the review process. Or to generate more hype. Or both.

They announced that it would be released next week, so I doubt they’ve only just started training it.

There will be Flash, 27B and 2 other models called Plus and Max.

They most likely used a local fork for a while.

I heard some people use adaptive kv streaming to fit large contexts. Unfortunately, it’s not merged into the upstream yet.