Magpie-Qwen-DiMind-1.7B-GGUF

Magpie-Qwen-DiMind-1.7B is a compact yet powerful model for mathematical reasoning, code generation, and structured output tasks, built with a dual-intelligence architecture (DiMind) to handle both quick-response prompts and deep, multi-step problems. With a parameter size of 1.7B, it balances performance and efficiency, using 80% of the Magpie Pro 330k dataset and a modular blend of additional datasets for general-purpose and technical tasks.

ModelFile

File Name	Size	Description
Magpie-Qwen-DiMind-1.7B.BF16.gguf	3.45 GB	Model file in BF16 format
Magpie-Qwen-DiMind-1.7B.F16.gguf	3.45 GB	Model file in F16 format
Magpie-Qwen-DiMind-1.7B.F32.gguf	6.89 GB	Model file in F32 format
Magpie-Qwen-DiMind-1.7B.Q4_K_M.gguf	1.11 GB	Quantized model file (Q4_K_M)
Magpie-Qwen-DiMind-1.7B.Q5_K_M.gguf	1.26 GB	Quantized model file (Q5_K_M)
Magpie-Qwen-DiMind-1.7B.Q8_0.gguf	1.83 GB	Quantized model file (Q8_0)
.gitattributes	2.01 kB	Git attributes file
README.md	534 B	Documentation file
config.json	31 B	Configuration file

Quants Usage

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

Link	Type	Size/GB	Notes
GGUF	Q2_K	0.4
GGUF	Q3_K_S	0.5
GGUF	Q3_K_M	0.5	lower quality
GGUF	Q3_K_L	0.5
GGUF	IQ4_XS	0.6
GGUF	Q4_K_S	0.6	fast, recommended
GGUF	Q4_K_M	0.6	fast, recommended
GGUF	Q5_K_S	0.6
GGUF	Q5_K_M	0.7
GGUF	Q6_K	0.7	very good quality
GGUF	Q8_0	0.9	fast, best quality
GGUF	f16	1.6	16 bpw, overkill

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