123
https://qwen.ai/blog?id=qwen3.8
The model weights will be open-sourced on Hugging Face and ModelScope next week — stay tuned.
I'm hoping they also release a new 35b a3b, for us VRAM poors, a new 9b would also be great!
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 03 Aug 2026
123 points (93.6% liked)
LocalLLaMA
5007 readers
37 users here now
Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
Get support from the community! Ask questions, share prompts, discuss benchmarks, get hyped at the latest and greatest model releases! Enjoy talking about our awesome hobby.
As ambassadors of the self-hosting machine learning community, we strive to support each other and share our enthusiasm in a positive constructive way.
Rules:
Rule 1 - No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.
Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.
Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.
Rule 4 - No implying that models are devoid of purpose or potential for enriching peoples lives.
founded 3 years ago
MODERATORS
It has indeed been really good, so much better than similarly sized models a few years ago. Would be interesting to know how far it is from what is possible to fit into a 27b model.
I'm using Gemma4:26b as of right now. Only using it as a conversation agent in home assistant with MCP tool usage.
Has anyone compared gemma and qwen in combination with home assistant and has an opinion?
I've found Qwen 27b better adheres to rules and tool calls, but that depends on lots of things.
One that a bit of a dark horse is Arcee Trinity Mini (26B-A3B)
https://huggingface.co/arcee-ai/Trinity-Mini-GGUF
On paper it's not in the same bookclub as the others (unless that bookclub involved eating books) but it is obedient with tool calls IMHE
Gemma is probably good for that, as long as it's consistently succeeding at the tool calls.
I'd say its above 95% success rate for me personally