Unverified50% confidenceOpinionExact time
For most users with limited VRAM, Q4_K_M is the most cost-effective quantization choice.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/22/2026
First Seen
Valid until: 10/20/2026
Sources
Ollama本地部署大模型：Windows完整安装教程
Related Claims
UnverifiedQ4_K_M (4-bit quantization, K-means optimized) is currently the best overall choice, with a precision loss of approximately 2–5%, and is the most widely used quantization format in the community.79% similarUnverifiedQ4_K_M往往是本地部署时性价比最高的首选方案，实测困惑度损失通常不超过1%78% similarUnverifiedQ4 quantization is considered the best balance between quality and size, and is the most cost-effective choice for most developers.76% similarUnverifiedRecommended quantization gradient choices: Q8 is nearly lossless but has the largest footprint, Q6/Q5 are the sweet spot between quality and size, Q4_K_M is the default download version for most users, and the Q2/IQ series is suitable for use when the model barely fits.74% similarUnverifiedFor RTX 4090 users, Q4_K_M or Q5_K_M is generally the best balance point between precision and speed73% similar
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