Post
39
Hi guys.
We're announcing Klein SL Pro, our new model at Klein ML.
It's doing post-training of Qwen3.8 Flash Next to make IT fit on 16GB VRAM.
It works by converting its MoE to SLMoE, SLMoE is an architecture, that chooses experts per response, not per token anymore.
This makes it so you can offload everything else to the disk and not get slow speed.
We're also seeking more compute to do this same thing on Deepseek V4.1 Flash, allowing it to run on 16GB VRAM tightly and definitely on 24GB. If you have hardware, more than 200B of VRAM in total, create a discussion klein-ml/README.
We're announcing Klein SL Pro, our new model at Klein ML.
It's doing post-training of Qwen3.8 Flash Next to make IT fit on 16GB VRAM.
It works by converting its MoE to SLMoE, SLMoE is an architecture, that chooses experts per response, not per token anymore.
This makes it so you can offload everything else to the disk and not get slow speed.
We're also seeking more compute to do this same thing on Deepseek V4.1 Flash, allowing it to run on 16GB VRAM tightly and definitely on 24GB. If you have hardware, more than 200B of VRAM in total, create a discussion klein-ml/README.