Unverified50% confidenceFactExact time
7B–9B parameter models typically occupy 5–7 GB of VRAM after Q4 or Q5 quantization.
1
Sources
50%
Confidence
Long-term
Relevance
9/24/2026
First Seen
Sources
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Related Claims
UnverifiedThe Q4_K_M quantization scheme averages approximately 4.8 bits per weight, while the Q8_0 quantization scheme uses 8 bits per weight.79% similarUnverifiedQ6_K 使用 6-bit 量化并结合 K-quants 分组技术，相比 Q4 量化损失更小，相比 Q8 量化体积更小78% similarUnverifiedQwen2.5-Coder 7B is one of the strongest models in terms of coding capability at the 7B level, with approximately 5 GB of VRAM usage after Q4 quantization.75% similarVerifiedQ4量化将每个权重参数从16位压缩到4位，理论上可将模型体积缩小约75%75% 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% similar
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