license, base_model, language, pipeline_tag, library_name, tags
| license | base_model | language | pipeline_tag | library_name | tags | ||||
|---|---|---|---|---|---|---|---|---|---|
| apache-2.0 |
|
|
text-generation | transformers |
|
Demeter-LongCoT-Qwen3-1.7B-GGUF
Demeter-LongCoT-Qwen3-1.7B is a reasoning-focused model fine-tuned on Qwen/Qwen3-1.7B using the Demeter-LongCoT-400K dataset. It is designed for math and code chain-of-thought reasoning, blending symbolic precision, scientific logic, and structured output fluency—making it an effective tool for developers, educators, and researchers seeking reliable step-by-step reasoning.
Model Files
| File Name | Quant Type | File Size |
|---|---|---|
| Demeter-LongCoT-Qwen-1.7B.BF16.gguf | BF16 | 3.45 GB |
| Demeter-LongCoT-Qwen-1.7B.F16.gguf | F16 | 3.45 GB |
| Demeter-LongCoT-Qwen-1.7B.F32.gguf | F32 | 6.89 GB |
| Demeter-LongCoT-Qwen-1.7B.Q2_K.gguf | Q2_K | 778 MB |
| Demeter-LongCoT-Qwen-1.7B.Q3_K_L.gguf | Q3_K_L | 1 GB |
| Demeter-LongCoT-Qwen-1.7B.Q3_K_M.gguf | Q3_K_M | 940 MB |
| Demeter-LongCoT-Qwen-1.7B.Q3_K_S.gguf | Q3_K_S | 867 MB |
| Demeter-LongCoT-Qwen-1.7B.Q4_0.gguf | Q4_0 | 1.05 GB |
| Demeter-LongCoT-Qwen-1.7B.Q4_1.gguf | Q4_1 | 1.14 GB |
| Demeter-LongCoT-Qwen-1.7B.Q4_K.gguf | Q4_K | 1.11 GB |
| Demeter-LongCoT-Qwen-1.7B.Q4_K_M.gguf | Q4_K_M | 1.11 GB |
| Demeter-LongCoT-Qwen-1.7B.Q4_K_S.gguf | Q4_K_S | 1.06 GB |
| Demeter-LongCoT-Qwen-1.7B.Q5_0.gguf | Q5_0 | 1.23 GB |
| Demeter-LongCoT-Qwen-1.7B.Q5_1.gguf | Q5_1 | 1.32 GB |
| Demeter-LongCoT-Qwen-1.7B.Q5_K.gguf | Q5_K | 1.26 GB |
| Demeter-LongCoT-Qwen-1.7B.Q5_K_M.gguf | Q5_K_M | 1.26 GB |
| Demeter-LongCoT-Qwen-1.7B.Q5_K_S.gguf | Q5_K_S | 1.23 GB |
| Demeter-LongCoT-Qwen-1.7B.Q6_K.gguf | Q6_K | 1.42 GB |
| Demeter-LongCoT-Qwen-1.7B.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):
