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Mistral AI · Dense · GQA

Mistral Small 24B Instruct 2501:各量化与上下文下的显存

23.6B 参数、40 层、8 个 KV 头。换算成 GB 是这个结果。

23.6B parameters 14.2 GB at Q4_K_M 40 layers 8 KV heads
架构参数
Parameters23.6BVendor model card
Layers40config.json
Hidden size5120config.json
Attention heads32config.json
KV heads8config.json (GQA)
Head dim128config.json
Max context32768 tokensconfig.json

Source: mistralai/Mistral-Small-24B-Instruct-2501 config.json

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
47.2 GB1.3 GB50.0 GBMac Studio M4 Max 128GB
INT8 / Q8_0
1.06 B/param
25.0 GB1.3 GB27.9 GBMac Studio M4 Max 128GB
Q4_K_M (4-bit)
0.6 B/param
14.2 GB1.3 GB17.0 GBMac Studio M4 Max 128GB
Q5_K_M (5-bit)
0.72 B/param
17.0 GB1.3 GB19.8 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
4k0.7 GB16.3 GBMac Studio M4 Max 128GB
8k1.3 GB17.0 GBMac Studio M4 Max 128GB
16k2.7 GB18.3 GBMac Studio M4 Max 128GB
32k5.4 GB21.0 GBMac Studio M4 Max 128GB
64k10.7 GB26.4 GBMac Studio M4 Max 128GB
128k21.5 GB37.1 GBMac Studio M4 Max 128GB

结论

At Q4_K_M the weights alone are about 14.2 GB. With 8K of context and 1.5 GB of runtime overhead it lands near 17.0 GB. It fits: RTX 4090, RTX 3090, RTX 5090, 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。