prithivMLmods/Magpie-Qwen-DiMind-1.7B-GGUF
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Model: prithivMLmods/Magpie-Qwen-DiMind-1.7B-GGUF
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---
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Magpie-Qwen-DiMind-1.7B
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- math
- code
- reasoning
---
# 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](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q2_K.gguf) | Q2_K | 0.4 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_S.gguf) | Q3_K_S | 0.5 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_M.gguf) | Q3_K_M | 0.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_L.gguf) | Q3_K_L | 0.5 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.IQ4_XS.gguf) | IQ4_XS | 0.6 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q4_K_S.gguf) | Q4_K_S | 0.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q4_K_M.gguf) | Q4_K_M | 0.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_S.gguf) | Q5_K_S | 0.6 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_M.gguf) | Q5_K_M | 0.7 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q6_K.gguf) | Q6_K | 0.7 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q8_0.gguf) | Q8_0 | 0.9 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.f16.gguf) | f16 | 1.6 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)