Alcoft/dnotitia_Smoothie-Qwen3-1.7B-GGUF
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ModelHub XC 800860913f 初始化项目，由ModelHub XC社区提供模型 
Model: Alcoft/dnotitia_Smoothie-Qwen3-1.7B-GGUF
Source: Original Platform
2026-10-26 18:26:17 +08:00

6.9 KiB
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base_model, pipeline_tag, language, license, tags
base_model pipeline_tag language license tags
dnotitia/Smoothie-Qwen3-1.7B
text-generation
en
apache-2.0
dnotitia
nlp
llm
conversation
chat
reasoning
Quant Size Description
Q2_K_XXS 595.71 MB Not recommended for most people. Extremelly low quality.
Q2_K_XS 595.71 MB Not recommended for most people. Very low quality.
Q2_K 595.71 MB Not recommended for most people. Very low quality.
Q2_K_L 813.63 MB Not recommended for most people. Uses Q8_0 for output and embedding, and Q2_K for everything else. Very low quality.
Q2_K_XL 1.07 GB Not recommended for most people. Uses F16 for output and embedding, and Q2_K for everything else. Very low quality.
Q3_K_XXS 711.16 MB Not recommended for most people. Prefer any bigger Q3_K quantization. Very low quality.
Q3_K_XS 711.16 MB Not recommended for most people. Prefer any bigger Q3_K quantization. Very low quality.
Q3_K_S 711.16 MB Not recommended for most people. Prefer any bigger Q3_K quantization. Low quality.
Q3_K_M 780.1 MB Not recommended for most people. Low quality.
Q3_K_L 841.1 MB Not recommended for most people. Low quality.
Q3_K_XL 1.0 GB Not recommended for most people. Uses Q8_0 for output and embedding, and Q3_K_L for everything else. Low quality.
Q3_K_XXL 1.28 GB Not recommended for most people. Uses F16 for output and embedding, and Q3_K_L for everything else. Low quality.
Q4_K_XS 934.57 MB Lower quality than Q4_K_S.
Q4_K_S 934.57 MB Recommended. Slightly low quality.
Q4_K_M 979.6 MB Recommended. Decent quality for most use cases.
Q4_K_L 1.1 GB Recommended. Uses Q8_0 for output and embedding, and Q4_K_M for everything else. Decent quality.
Q4_K_XL 1.37 GB Recommended. Uses F16 for output and embedding, and Q4_K_M for everything else. Decent quality.
Q5_K_XXS 1.11 GB Lower quality than Q5_K_S.
Q5_K_XS 1.11 GB Lower quality than Q5_K_S.
Q5_K_S 1.11 GB Recommended. High quality.
Q5_K_M 1.13 GB Recommended. High quality.
Q5_K_L 1.24 GB Recommended. Uses Q8_0 for output and embedding, and Q5_K_M for everything else. High quality.
Q5_K_XL 1.51 GB Recommended. Uses F16 for output and embedding, and Q5_K_M for everything else. High quality.
Q6_K_S 1.32 GB Lower quality than Q6_K.
Q6_K 1.32 GB Recommended. Very high quality.
Q6_K_L 1.39 GB Recommended. Uses Q8_0 for output and embedding, and Q6_K for everything else. Very high quality.
Q6_K_XL 1.66 GB Recommended. Uses F16 for output and embedding, and Q6_K for everything else. Very high quality.
Q8_K_XS 1.71 GB Lower quality than Q8_0.
Q8_K_S 1.71 GB Lower quality than Q8_0.
Q8_0 1.71 GB Recommended. Quality almost like F16.
Q8_K_XL 1.98 GB Recommended. Uses F16 for output and embedding, and Q8_0 for everything else. Quality almost like F16.
F16 3.21 GB Not recommended. Overkill. Prefer Q8_0.
ORIGINAL (BF16) 3.21 GB Not recommended. Overkill. Prefer Q8_0.

Quantized using TAO71-AI AutoQuantizer. You can check out the original model card here.