221–223 of 223 posts
I wish AI slop articles were somehow automatically flagged and deaded. They're all flowery verbose piles of crap. Yeah, the model is interesting, but the article is trash. I can't believe real humans are willing to sign their name to this stuff.
I test drove it yesterday. It's pretty impressive at 8b. Runs on commodity hardware quickly. Qwen3.6 35b a3b is still my local champion but I may use this for auto complete and small tasks. Granite has recent training data which is nice. If the other small models got fine tuned on recent data I don't know if I would use this at all, but that alone makes it pretty decent. The 4b they released was not good for my needs…
> Qwen3.6 35b a3b is still my local champion but I may use this for auto complete and small tasks. I second this! Using the Unsloth Q6 (I forgot the exact name). Currently using it with forgecode (with zsh), on my Strix Halo, and it's suprisingly really good. I would say slightly Similar to Haiku 4.5, plus additional privacy, minus speed. It's surprisingly really fast for the hardware, given the speculative decoding,…
Earlier quoted context omitted.
Qwen 3.6 burns it to the ground. it was not even a challenge. Gemma4 seriously fails at toolcalls and agentic works. It got all messed up after 2-3 turns of Vibecoding.
How do you run it? vllm? llama.cpp? Can you share some parameters you enable tool calling and agentic usage? Or, higher level, some philosophies on what approaches you are using for tuning to get better tool calling and/or agentic usage? I'm having surprisingly good success with unsloth/Qwen3.6-27B-GGUF:Q4_K_M (love unsloth guys) on my RTX3090/24GB using opencode as the orchestrator. It concocts some misleading paths…
Both 27b and A3B done all my production works pbeautifuly (At Q8) i dont think any model are good for Q4.
Qwen 3.5 122b surpasses both of them tho.