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Meta · Dense · GQA

Llama 3.3 70B Instruct:各量化与上下文下的显存

70.6B 参数、80 层、8 个 KV 头。换算成 GB 是这个结果。

70.6B parameters 42.4 GB at Q4_K_M 80 layers 8 KV heads
架构参数
Parameters70.6BVendor model card
Layers80config.json
Hidden size8192config.json
Attention heads64config.json
KV heads8config.json (GQA)
Head dim128config.json
Max context131072 tokensconfig.json

Source: Meta Llama 3 architecture (published); repo gated

各量化精度下的显存
Total includes 8K of KV cache and 1.5 GB runtime overhead.
量化WeightsKV @ 8K总需求可运行于
FP16 / BF16
2.0 B/param
141.2 GB2.7 GB145.4 GB不行
INT8 / Q8_0
1.06 B/param
74.8 GB2.7 GB79.0 GBMac Studio M4 Max 128GB
Q4_K_M (4-bit)
0.6 B/param
42.4 GB2.7 GB46.5 GBMac Studio M4 Max 128GB
Q5_K_M (5-bit)
0.72 B/param
50.8 GB2.7 GB55.0 GBMac Studio M4 Max 128GB
各上下文长度下的 KV 缓存
Q4_K_M weights plus 1.5 GB overhead. KV cache at FP16.
上下文KV 缓存总需求可运行于
4k1.3 GB45.2 GBMac Studio M4 Max 128GB
8k2.7 GB46.5 GBMac Studio M4 Max 128GB
16k5.4 GB49.2 GBMac Studio M4 Max 128GB
32k10.7 GB54.6 GBMac Studio M4 Max 128GB
64k21.5 GB65.3 GBMac Studio M4 Max 128GB
128k42.9 GB86.8 GBMac Studio M4 Max 128GB

结论

At Q4_K_M the weights alone are about 42.4 GB. With 8K of context and 1.5 GB of runtime overhead it lands near 46.5 GB. It fits: Mac Studio M4 Max 128GB.

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所有吞吐数字均为基于内存带宽与公开实测的估算值,显存数字按模型架构与量化假设推算。购买硬件前请以你自己的运行环境为准。