Lacaille-MoT-4B-Supreme2-GGUF

Lacaille-MoT-4B-Supreme2 is a high-efficiency, multi-domain model fine-tuned on Qwen3-4B using the Mixture of Thoughts (MoT) dataset enhanced with code, math, science expert clusters and an extended open code reasoning dataset. This model blends symbolic precision, scientific logic, and structured output fluency—making it an ideal tool for developers, educators, and researchers seeking advanced reasoning under constrained compute.

Model File Table

File Name	Size	Format	Description
Lacaille-MoT-4B-Supreme2.BF16.gguf	8.05 GB	GGUF (BF16)	BFloat16 precision model file
Lacaille-MoT-4B-Supreme2.F16.gguf	8.05 GB	GGUF (F16)	Float16 precision model file
Lacaille-MoT-4B-Supreme2.F32.gguf	16.1 GB	GGUF (F32)	Float32 precision model file
Lacaille-MoT-4B-Supreme2.Q4_K_M.gguf	2.5 GB	GGUF (Q4_K_M)	4-bit quantized model file
Lacaille-MoT-4B-Supreme2.Q5_K_M.gguf	2.89 GB	GGUF (Q5_K_M)	5-bit quantized model file
Lacaille-MoT-4B-Supreme2.Q8_0.gguf	4.28 GB	GGUF (Q8_0)	8-bit quantized model file
config.json	31 B	JSON	Configuration file
.gitattributes	1.95 kB	Text	Git attributes configuration

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):