Running large language models (LLMs) on your local machine has become increasingly popular, offering privacy, offline access, and customization. Ollama is a ...
I got both IK and Croco built and running on Vulkan, but they both seem abysmally slow compared to Kobold, whether I run one of the GGUFs I already had or a trellis quant I just made. It’s using the GPU, so not sure why. I’ll keep an eye on the projects and try them again in the future.
Ah. You can still run them in exllamav2, but you’re probably better off with ik_llama.cpp then:
https://github.com/ikawrakow/ik_llama.cpp
It supports special “KT” quantizations, aka trellis quants similar to exllamav3, and will work with vulkan (or rocm?) on your 6800.
Quantizing yourself is not too bad, but if you want, just ping me, and I can make some 16GB KT quants, or point you to how to do it yourself.
It’s also a good candidate for Qwen3 30B with a little CPU offloading. ik_llama.cpp is specifically optimized for MoE offloading.
I got both IK and Croco built and running on Vulkan, but they both seem abysmally slow compared to Kobold, whether I run one of the GGUFs I already had or a trellis quant I just made. It’s using the GPU, so not sure why. I’ll keep an eye on the projects and try them again in the future.