alt Hacker NewsI don't really have the hardware to try it out, but I'm curious to see how Qwen3.5 stacks up against Gemma 4 in a comparison like this. Especially this model that was fine tuned to be good at tool calling that has more than 500k downloads as of this moment: https://huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-...
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I'm just some guy on hackernews, but I actually did try this on my DGX Spark. I went back to Gemma 4 after a few rounds. My orchestration model kept having to send the Qwen model back to fix mistakes that Gemma wouldn't have made. I wound up with less working code per hour due to the mistakes.
Technically, I use OpenWebUI with Ollama, so I used the weights below, but it should be the same.
https://ollama.com/kwangsuklee/Qwen3.5-27B-Claude-4.6-Opus-R...
It's rather surprising that a solo dev can squeeze more performance out of a model with rather humble resources vs a frontier lab. I'm skeptical of claims that such a fine-tuned model is "better" -- maybe on certain benchmarks, but overall?
FYI the latest iteration of that finetune is here: https://huggingface.co/Jackrong/Qwopus3.5-27B-v3
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Jackrong has published the finetuning steps here. It seems to be quite thorough with notebooks etc. I am going through it myself now...
https://github.com/R6410418/Jackrong-llm-finetuning-guide