Model Releases
I have just moved from MacBook M5 pro 48 GB to RTX3090
Using the RTX3090 on a linux machine I built for it and running Qwen 3.8 27B getting average 100t/s compared to my MacBook 20t/s I think I can finally get rid of my Claude subscription, this is good e
Using the RTX3090 on a linux machine I built for it and running Qwen 3.8 27B getting average 100t/s compared to my MacBook 20t/s I think I can finally get rid of my Claude subscription, this is good enough for me. I am a software dev and I can get what I need from this set up and be more productive. I am using the linux machine serving the model over an Open AI endpoint and using a custom build desktop app with pi behind it all. Regarding speeds average 20t/s on Mac with llama.cpp with mtp Unsloth Q6, Q4 on Mac didnt make much difference in speed for me. Linux running https://github.com/syv-ai/qwen38-27b-rtx3090 which is vLLM and a Q4 model I believe. Tool calls definitely fail more but qwen3.8 seems smart enough to fix and correct itself submitted by /u/gutard [link] [comments]
Related
- Anyone else amped up over Qwen 3.8?
- Compared Qwen 3.8 27B community quants on RTX 6000 vs Claude Opus 4.6
- 1x32GB V100 vs 2x16GB V100 vs 5060ti 16GB for QWEN 3.8
Source: r/LocalLLaMA | 2026-09-13