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Qwen2.5-Math-7B-Instruct-GGUF

Original Model

Qwen/Qwen2.5-Math-7B-Instruct

Run with LlamaEdge

  • LlamaEdge version: coming soon

Quantized GGUF Models

Name Quant method Bits Size Use case
Qwen2.5-Math-7B-Instruct-Q2_K.gguf Q2_K 2 3.02 GB smallest, significant quality loss - not recommended for most purposes
Qwen2.5-Math-7B-Instruct-Q3_K_L.gguf Q3_K_L 3 4.09 GB small, substantial quality loss
Qwen2.5-Math-7B-Instruct-Q3_K_M.gguf Q3_K_M 3 3.81 GB very small, high quality loss
Qwen2.5-Math-7B-Instruct-Q3_K_S.gguf Q3_K_S 3 3.49 GB very small, high quality loss
Qwen2.5-Math-7B-Instruct-Q4_0.gguf Q4_0 4 4.43 GB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2.5-Math-7B-Instruct-Q4_K_M.gguf Q4_K_M 4 4.68 GB medium, balanced quality - recommended
Qwen2.5-Math-7B-Instruct-Q4_K_S.gguf Q4_K_S 4 4.46 GB small, greater quality loss
Qwen2.5-Math-7B-Instruct-Q5_0.gguf Q5_0 5 5.32 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2.5-Math-7B-Instruct-Q5_K_M.gguf Q5_K_M 5 5.44 GB large, very low quality loss - recommended
Qwen2.5-Math-7B-Instruct-Q5_K_S.gguf Q5_K_S 5 5.32 GB large, low quality loss - recommended
Qwen2.5-Math-7B-Instruct-Q6_K.gguf Q6_K 6 6.25 GB very large, extremely low quality loss
Qwen2.5-Math-7B-Instruct-Q8_0.gguf Q8_0 8 8.21 GB very large, extremely low quality loss - not recommended
Qwen2.5-Math-7B-Instruct-f16.gguf f16 16 15.2 GB

Quantized with llama.cpp b3751

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GGUF
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qwen2

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Qwen/Qwen2.5-7B
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