Qwen3.8-Flash-Next 显存需求 131.53 GiB

显存需求 111.75 GiB–131.53 GiB。Qwen3.8-Flash-Next Q4_K_M，8,192 token。未选显卡，所以只是本地大模型的需求，不是能否装下。粗估 BF16 文件：359,999,963,128 字节。

Qwen/Qwen3.8-Flash-Next 检查点在本目录中的 BF16 safetensors 为 359,999,963,128 字节（335.28 GiB / 360.00 GB）。下载大小不是峰值显存，下面的数字是估算。

具体的模型版本，带来源的结构和权重文件信息。 GGUF Q4_K_M (bartowski)：8,192 个 token 下约 111.75 GiB–131.53 GiB，1 条序列，FP16 KV，llama.cpp。

当前结果是估算，不是对应环境的实测。未核实有文件依据的权重

能跑的设备

发布方与出处

激活参数未知，或没有独立来源。激活参数描述的是 token 路由计算量，不是完整驻留权重体积。

这次估算里的内存分层

文件字节、原始 KV、引擎额外占用和总需求是分开的。这不是一次运行时轨迹。

Weight artifact
111.39 GiB (119,599,030,080 bytes)
Raw KV cache
0.19 GiB (201,326,592 bytes)
Engine extras / workspace
0.18 GiB–19.95 GiB
Total estimated demand
111.75 GiB–131.53 GiB

计入的文件

量化计入的文件字节运行引擎证据
BF16 safetensors
bf16
131 个 safetensors 分片
选定字节合计：359,999,963,128 (335.28 GiB / 360.00 GB)
第一个分片：model-00001-of-00131.safetensors
最后一个分片：model-00131-of-00131.safetensors
查看全部 131 个分片文件
  • model-00001-of-00131.safetensors
  • model-00002-of-00131.safetensors
  • model-00003-of-00131.safetensors
  • model-00004-of-00131.safetensors
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  • model-00018-of-00131.safetensors
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359,999,963,128 (335.28 GiB / 360.00 GB)vllm, sglang, unspecifiedfile-metadata
GGUF Q8_0 (Unsloth)
gguf-q8_0
6 个 safetensors 分片
选定字节合计：188,225,033,248 (175.30 GiB / 188.23 GB)
第一个分片：Q8_0/Qwen3.8-Flash-Next-Q8_0-00001-of-00006.gguf
最后一个分片：Q8_0/Qwen3.8-Flash-Next-Q8_0-00006-of-00006.gguf
查看全部 6 个分片文件
  • Q8_0/Qwen3.8-Flash-Next-Q8_0-00001-of-00006.gguf
  • Q8_0/Qwen3.8-Flash-Next-Q8_0-00002-of-00006.gguf
  • Q8_0/Qwen3.8-Flash-Next-Q8_0-00003-of-00006.gguf
  • Q8_0/Qwen3.8-Flash-Next-Q8_0-00004-of-00006.gguf
  • Q8_0/Qwen3.8-Flash-Next-Q8_0-00005-of-00006.gguf
  • Q8_0/Qwen3.8-Flash-Next-Q8_0-00006-of-00006.gguf
188,225,033,248 (175.30 GiB / 188.23 GB)llama.cpp, ollama, unspecifiedfile-metadata
GGUF Q4_K_M (bartowski)
gguf-q4_k_m
Qwen3.8-Flash-Next-Q4_K_M/Qwen3.8-Flash-Next-Q4_K_M-00001-of-00004.gguf, Qwen3.8-Flash-Next-Q4_K_M/Qwen3.8-Flash-Next-Q4_K_M-00002-of-00004.gguf, Qwen3.8-Flash-Next-Q4_K_M/Qwen3.8-Flash-Next-Q4_K_M-00003-of-00004.gguf, Qwen3.8-Flash-Next-Q4_K_M/Qwen3.8-Flash-Next-Q4_K_M-00004-of-00004.gguf119,599,030,080 (111.39 GiB / 119.60 GB)llama.cpp, ollama, unspecifiedfile-metadata
GGUF Q5_K_M (bartowski)
gguf-q5_k_m
Qwen3.8-Flash-Next-Q5_K_M/Qwen3.8-Flash-Next-Q5_K_M-00001-of-00004.gguf, Qwen3.8-Flash-Next-Q5_K_M/Qwen3.8-Flash-Next-Q5_K_M-00002-of-00004.gguf, Qwen3.8-Flash-Next-Q5_K_M/Qwen3.8-Flash-Next-Q5_K_M-00003-of-00004.gguf, Qwen3.8-Flash-Next-Q5_K_M/Qwen3.8-Flash-Next-Q5_K_M-00004-of-00004.gguf134,668,639,040 (125.42 GiB / 134.67 GB)llama.cpp, ollama, unspecifiedfile-metadata
GGUF Q6_K (bartowski)
gguf-q6_k
5 个 safetensors 分片
选定字节合计：168,113,805,248 (156.57 GiB / 168.11 GB)
第一个分片：Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00001-of-00005.gguf
最后一个分片：Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00005-of-00005.gguf
查看全部 5 个分片文件
  • Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00001-of-00005.gguf
  • Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00002-of-00005.gguf
  • Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00003-of-00005.gguf
  • Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00004-of-00005.gguf
  • Qwen3.8-Flash-Next-Q6_K/Qwen3.8-Flash-Next-Q6_K-00005-of-00005.gguf
168,113,805,248 (156.57 GiB / 168.11 GB)llama.cpp, ollama, unspecifiedfile-metadata
INT4 theoretical没有已发布的文件89,999,990,730 (理论行不是可下载的发布文件。)—theoretical

按量化与上下文查看显存

并发序列数为 1。KV 默认 FP16。区间包含所列引擎已记录的运行时额外占用。这些数字与交互式计算器使用同一套核心。

量化2,048 tokens8,192 tokens32,768 tokens
BF16 safetensors336.00 GiB–388.56 GiB336.14 GiB–388.73 GiB336.70 GiB–389.39 GiB
GGUF Q8_0 (Unsloth)175.52 GiB–206.32 GiB175.66 GiB–206.50 GiB176.23 GiB–207.19 GiB
GGUF Q4_K_M (bartowski)111.61 GiB–131.35 GiB111.75 GiB–131.53 GiB112.31 GiB–132.22 GiB
GGUF Q5_K_M (bartowski)125.64 GiB–147.81 GiB125.79 GiB–147.99 GiB126.35 GiB–148.68 GiB
GGUF Q6_K (bartowski)156.79 GiB–184.35 GiB156.93 GiB–184.53 GiB157.50 GiB–185.22 GiB
INT4 theoretical
理论行不是可下载的发布文件。
84.04 GiB–108.65 GiB84.18 GiB–108.83 GiB84.75 GiB–109.52 GiB

KV Cache（原始数据）

用这个模型打开计算器

相关页面

数据来源

影响结论的假设

计算器

正在加载已发布的目录快照…

先选择模型，再检查设备。

量化

设备类型

工作负载

上下文长度主要影响 KV Cache 内存。

高级设置
运行时

这次估算使用的引擎和 KV 缓存类型。

工作负载

开销场景，以及是否计入预填充工作区。

拓扑

模型如何切到多张设备上。各设备的显存不会相加。

副本数是高级部署选项。数量指节点或 GPU，不是副本。

预算

系统保留和安全余量。数字框清空时保留上一次的值。

GiB（2^30 字节）

%

自定义模型

导入配置或手填结构。点导入之前不会去扫描仓库。

仅在浏览器中解析，不会上传文件。

只允许 huggingface.co 上的 config.json，不使用 token，不读取私有仓库。

搜索或选择目录中的模型，查看本地大模型的显存需求。

搜索或选择目录中的模型，查看本地大模型的显存需求。