Unverified60% confidenceFactExact time
Q3 quantization means each parameter is stored using approximately 3 bits
2
Sources
60%
Confidence
Long-term
Relevance
8/9/2026
First Seen
Sources
本地跑DeepSeek前沿模型：24GB显卡也能玩转
Related Claims
Verified4-bit quantization (such as Q4_K_M) can typically compress the memory footprint of a 3B model from approximately 6GB to approximately 2GB, with a precision loss of less than 2–3%.74% similarVerifiedQLoRA quantizes the base model weights in 4-bit NF4 format, making it possible to fine-tune a 13-billion-parameter model on a single GPU.73% similarVerifiedQ4_K_M uses mixed precision, storing some critical weights at 6-bit and the remainder at 4-bit, with an overall average of approximately 4.5-bit.71% similarVerifiedThe Q5_K_M quantization scheme averages approximately 5.3 bits per weight, and a 32B parameter model requires approximately 20–24GB of storage space after quantization.69% similarUnverified一个32K上下文窗口在Q4量化模型上可能额外占用2-4GB内存69% similar
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