Gacrux-R1-Qwen3-1.7B-MoD-GGUF/README.md

license, datasets, language, base_model, pipeline_tag, library_name, tags

license	datasets	language	base_model	pipeline_tag	library_name	tags
apache-2.0	prithivMLmods/Gargantua-R1-Wee	en zh	prithivMLmods/Gacrux-R1-Qwen3-1.7B-MoD	text-generation	transformers	text-generation-inference

Gacrux-R1-Qwen3-1.7B-MoD-GGUF

Gacrux-R1-Qwen3-1.7B-MoD is a high-efficiency, multi-domain model fine-tuned on Qwen3-1.7B with traces of Mixture of Domains (MoD). It leverages the prithivMLmods/Gargantua-R1-Wee dataset, designed for rigorous mathematical problem-solving and enriched with multi-domain coverage across mathematics, coding, and science. 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 Files

File Name	Quant Type	File Size
Gacrux-R1-Qwen3-1.7B-MoD.BF16.gguf	BF16	3.45 GB
Gacrux-R1-Qwen3-1.7B-MoD.F16.gguf	F16	3.45 GB
Gacrux-R1-Qwen3-1.7B-MoD.F32.gguf	F32	6.89 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q2_K.gguf	Q2_K	778 MB
Gacrux-R1-Qwen3-1.7B-MoD.Q3_K_L.gguf	Q3_K_L	1 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q3_K_M.gguf	Q3_K_M	940 MB
Gacrux-R1-Qwen3-1.7B-MoD.Q3_K_S.gguf	Q3_K_S	867 MB
Gacrux-R1-Qwen3-1.7B-MoD.Q4_K_M.gguf	Q4_K_M	1.11 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q4_K_S.gguf	Q4_K_S	1.06 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q5_K_M.gguf	Q5_K_M	1.26 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q5_K_S.gguf	Q5_K_S	1.23 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q6_K.gguf	Q6_K	1.42 GB
Gacrux-R1-Qwen3-1.7B-MoD.Q8_0.gguf	Q8_0	1.83 GB

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):