File size: 4,153 Bytes
5f93759 b2a18b4 579b487 aea95a5 5976ae0 aea95a5 5976ae0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | ---
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Open-Xi-Math-Preview
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- math
---
# **Open-Xi-Math-Preview-GGUF**
> **Open-Xi-Math-Preview** is a **mathematics-focused reasoning model** fine-tuned on **Qwen2-1.5B-Instruct**, utilizing a **modular dataset** designed for enhancing **mathematical thinking**. It provides robust capabilities in symbolic reasoning, structured deduction, and compact coding — optimized for edge deployment on **resource-constrained devices**.
## Model Files
| File Name | Size | Quantization | Format | Description |
| ---------------------------------- | ------- | ------------ | ------ | ----------------------------- |
| `Open-Xi-Math-Preview.BF16.gguf` | 3.56 GB | BF16 | GGUF | BFloat16 precision version |
| `Open-Xi-Math-Preview.F16.gguf` | 3.56 GB | FP16 | GGUF | Float16 precision version |
| `Open-Xi-Math-Preview.F32.gguf` | 7.11 GB | FP32 | GGUF | Float32 precision version |
| `Open-Xi-Math-Preview.Q2_K.gguf` | 753 MB | Q2\_K | GGUF | 2-bit quantized (K variant) |
| `Open-Xi-Math-Preview.Q3_K_M.gguf` | 924 MB | Q3\_K\_M | GGUF | 3-bit quantized (K M variant) |
| `Open-Xi-Math-Preview.Q4_K_M.gguf` | 1.12 GB | Q4\_K\_M | GGUF | 4-bit quantized (K M variant) |
| `Open-Xi-Math-Preview.Q4_K_S.gguf` | 1.07 GB | Q4\_K\_S | GGUF | 4-bit quantized (K S variant) |
| `Open-Xi-Math-Preview.Q5_K_M.gguf` | 1.29 GB | Q5\_K\_M | GGUF | 5-bit quantized (K M variant) |
| `Open-Xi-Math-Preview.Q5_K_S.gguf` | 1.26 GB | Q5\_K\_S | GGUF | 5-bit quantized (K S variant) |
| `Open-Xi-Math-Preview.Q6_K.gguf` | 1.46 GB | Q6\_K | GGUF | 6-bit quantized (K variant) |
| `Open-Xi-Math-Preview.Q8_0.gguf` | 1.89 GB | Q8\_0 | GGUF | 8-bit quantized |
| `.gitattributes` | 2.39 kB | — | — | Git LFS tracking file |
| `config.json` | 31 B | — | — | Configuration file |
| `README.md` | 4.29 kB | — | — | Model documentation |
## 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):
 |