Comment by erelong
7 days ago
I was trying Ornith 9B locally (it's up on Ollama) which claims:
> Ornith-1.0-9B, which can be easily deployed on edge devices, matches or exceeds the performance of much larger models such as Gemma 4-31B and Qwen 3.6 35B.
https://deep-reinforce.com/ornith_1_0.html
Only tried it so much so far; it did a little better than Qwen 9B
Orinth was not impressive in my vibes testing, I just completed my first grid analysis with real evals on qwen 27b. I can now scale that grid analysis and intend to include the qwen 9b ftunes I've seen going around. They were actually a main motivation because so many claim this or that one is better, but very little in the way of evals
I tried it, too, and it got stuck in some loops where it couldn’t recover. Shame, it was promising for the same reason as Bonsai’s models.
check out geyron-9b, I've only used it a bit, but seems better than orinth on vibe evals
huggingface.co/Tivaphraen/Geryon-9B-v1
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Note that 3.5 9B cannot do thinking (while 3.6 27B can, pretty effectively, quite verbosely).
3.5 9B can do thinking. Its just disabled by default in its gguf chat template.
It is disabled because it doesn't work :) Try it and see the doom loop it gets itself in.
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Is that a 1-bit LLM? I don’t understand the connection with this article.
Oh, I don't actually know the difference if you want to explain it
The title says it's 27B grade running on a phone and what I was comparing it to in my mind was a model that runs at 35B grade that could presumably run on a phone "better"?
edit: I asked AI for the difference and understand a little better, thanks for the heads up to learn the difference between models... I think the thing was, although ornith was created for a specific agentic purpose, it was still outperforming a previous generalist model I had running locally (so in my mind I thought it was still a better local model) - I'd like to try bonsai out if I can figure out how to run it lol