Qwen-2.5 GGUF Models
Collection
LlamaEdge compatible quants for Qwen 2.5 instruct and coder models.
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9 items
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Updated
LlamaEdge version: v0.14.3
Prompt template
Prompt type: chatml
Prompt string
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Context size: 128000
Run as LlamaEdge service
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-14B-Instruct-Q5_K_M.gguf \
llama-api-server.wasm \
--model-name Qwen2.5-14B-Instruct \
--prompt-template chatml \
--ctx-size 128000
Run as LlamaEdge command app
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-14B-Instruct-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template chatml \
--ctx-size 128000
Name | Quant method | Bits | Size | Use case |
---|---|---|---|---|
Qwen2.5-14B-Instruct-Q2_K.gguf | Q2_K | 2 | 5.77 GB | smallest, significant quality loss - not recommended for most purposes |
Qwen2.5-14B-Instruct-Q3_K_L.gguf | Q3_K_L | 3 | 7.92 GB | small, substantial quality loss |
Qwen2.5-14B-Instruct-Q3_K_M.gguf | Q3_K_M | 3 | 7.34 GB | very small, high quality loss |
Qwen2.5-14B-Instruct-Q3_K_S.gguf | Q3_K_S | 3 | 6.66 GB | very small, high quality loss |
Qwen2.5-14B-Instruct-Q4_0.gguf | Q4_0 | 4 | 8.52 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Qwen2.5-14B-Instruct-Q4_K_M.gguf | Q4_K_M | 4 | 8.99 GB | medium, balanced quality - recommended |
Qwen2.5-14B-Instruct-Q4_K_S.gguf | Q4_K_S | 4 | 8.57 GB | small, greater quality loss |
Qwen2.5-14B-Instruct-Q5_0.gguf | Q5_0 | 5 | 10.3 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Qwen2.5-14B-Instruct-Q5_K_M.gguf | Q5_K_M | 5 | 10.5 GB | large, very low quality loss - recommended |
Qwen2.5-14B-Instruct-Q5_K_S.gguf | Q5_K_S | 5 | 10.3 GB | large, low quality loss - recommended |
Qwen2.5-14B-Instruct-Q6_K.gguf | Q6_K | 6 | 12.1 GB | very large, extremely low quality loss |
Qwen2.5-14B-Instruct-Q8_0.gguf | Q8_0 | 8 | 15.1 GB | very large, extremely low quality loss - not recommended |
Qwen2.5-14B-Instruct-f16.gguf | f16 | 16 | 29.5 GB |
Quantized with llama.cpp b3751