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

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liuliu 2 hours ago | parent | next [-]

Note that 3.5 9B cannot do thinking (while 3.6 27B can, pretty effectively, quite verbosely).

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gunalx 36 minutes ago | parent [-]

3.5 9B can do thinking. Its just disabled by default in its gguf chat template.

	▲	liuliu 4 minutes ago \| parent [-]
		It is disabled because it doesn't work :) Try it and see the doom loop it gets itself in.

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verdverm 32 minutes ago | parent | prev | next [-]

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

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janalsncm 2 hours ago | parent | prev [-]

Is that a 1-bit LLM? I don’t understand the connection with this article.

	▲	erelong an hour ago \| parent [-]
		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