I tested qwen3.5 122b when it went out, I really liked it and for my development tests it was on pair to gemini 3 flash (my current AI tool for coding) so I was looking for hardware investing, the problem is I need a new mobo and 1 (or 2 more 3090) and the price is just too high right now.
I saw a lot of posts saying that qwen3.5 27b was better than 122b it actually didn't made sense to me, then I saw nemotron 3 super 120b but people said it was not better than qwen3.5 122b, I trusted them.
Yesterday and today I tested all these models:
"unsloth/Qwen3.5-27B-GGUF:UD-Q4_K_XL"
"unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL"
"unsloth/Qwen3.5-122B-A10B-GGUF"
"unsloth/Qwen3.5-27B-GGUF:UD-Q6_K_XL"
"unsloth/Qwen3.5-27B-GGUF:UD-Q8_K_XL"
"unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF:UD-IQ4_XS"
"unsloth/gpt-oss-120b-GGUF:F16"
I also tested against gpt-5.4 high so I can compare them better.
To my sorprise nemotron was very, very good model, on par with gpt-5.4 and also qwen3.5-25b did great as well.
Sadly (but also good) gpt-oss 120b and qwen3.5 122b performed worse than the other 2 models (good because they need more hardware).
So I can finally use "Qwen3.5-27B-GGUF:UD-Q6_K_XL" for real developing tasks locally, the best is I don't need to get more hardware (I already own 2x 3090).
I am sorry for not providing too much info but I didn't save the tg/pp for all of them, nemotron ran at 80 tg and about 2000 pp, 100k context on vast.ai with 4 rtx 3090 and Qwen3.5-27B Q6 at 803pp, 25 tg, 256k context on vast.ai as well.
I'll setup it locally probably next week for production use.
These are the commands I used (pretty much copied from unsloth page):
./llama.cpp/llama-server -hf unsloth/Qwen3.5-27B-GGUF:UD-Q6_K_XL --ctx-size 262144 --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0.00 -ngl 999 P.D.
I am so glad I can actually replace API subscriptions (at least for the daily tasks), I'll continue using CODEX for complex tasks.
If I had the hardware that nemotron-3-super 120b requires, I would use it instead, it also responded always on my own language (Spanish) while others responded on English.
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