--- license: apache-2.0 language: - en base_model: - prithivMLmods/Nenque-MoT-0.6B-Elite14 pipeline_tag: text-generation library_name: transformers tags: - text-generation-inference - math - thinking --- # **Nenque-MoT-0.6B-Elite14-GGUF** > **Nenque-MoT-0.6B-Elite14** is a compact, high-efficiency model tailored for **mathematical reasoning**, **code generation**, and **structured technical inference**. Fine-tuned from **Qwen3-0.6B** using the **MoT (Mixture of Thoughts) dataset**—with a focus on **math expert clusters**—this model delivers strong symbolic performance in low-resource environments. Despite its **0.6B parameter** size, it offers elite-level precision across STEM and multilingual technical domains. ## Model File | File Name | Size | Format | Description | |--------------------------------------------|--------|---------------|-----------------------------------------| | Nenque-MoT-0.6B-Elite14.BF16.gguf | 1.2 GB | GGUF (BF16) | BFloat16 precision model file | | Nenque-MoT-0.6B-Elite14.F16.gguf | 1.2 GB | GGUF (F16) | Float16 precision model file | | Nenque-MoT-0.6B-Elite14.Q4_K_M.gguf | 397 MB | GGUF (Q4_K_M) | 4-bit quantized model file | | Nenque-MoT-0.6B-Elite14.Q5_K_M.gguf | 444 MB | GGUF (Q5_K_M) | 5-bit quantized model file | | unsloth.Q8_0.gguf | 639 MB | GGUF (Q8_0) | 8-bit quantized model file | | config.json | 31 B | JSON | Configuration file | | .gitattributes | 1.86 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): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)