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Text model · DeepSeek-V4

DeepSeek-V4-Flash: RAM and VRAM requirements

DeepSeek-V4-Flash needs about 179.7 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~174.87 GB to download; KV cache and overhead add the rest), or about 307.1 GB at Q8_0. The lightest hardware that runs it is Apple M3 Ultra (256GB).

DeepSeek-V4 family · 284B params (Mixture-of-Experts: activates only 13B of 284B params per token, so generation is faster than the total size suggests) · released Apr 2026.

Shopping for hardware? See what runs DeepSeek-V4-Flash →

License MIT · Commercial OK ↓ 2.7M/mo ♥ 2K on HuggingFace
Q4_K_M GGUF
174.87 GB
Q8_0 GGUF
302.27 GB
Memory @ Q4 (4k)
~179.7 GB
Context
1000 k

Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.

Will it run on your device?

DeepSeek-V4-Flash runs on 1 of 40 tracked devices at Q4_K_M.

0 run well 1 tight fit 39 too small
Fit check Q4_K_M
No, not enough memory
needs 179.7 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)174.87 GB
+
KV cache (4k)4 GB
+
Overhead0.8 GB
=
Total179.7 GB

How context length changes it

4k context ~179.7 GB 32k context ~208.1 GB 128k context ~305.1 GB

Longer context grows the KV cache, which for DeepSeek-V4-Flash is sized by its 13B active params, not the full 284B. It needs ~179.7 GB at 4k and ~305.1 GB at 128k.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 118.9 GB est
Q3_K_M 138.8 GB est
Q4_K_M (default) 174.87 GB
Q5_K_M 202.4 GB est
Q6_K 232.9 GB est
Q8_0 302.27 GB
FP16 568 GB est

Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.

Run it

llama.cpp
$ llama-cli -hf teamblobfish/DeepSeek-V4-Flash-GGUF:Q4_K_M
LM Studio
$ lms get teamblobfish/DeepSeek-V4-Flash-GGUF

Which devices can run DeepSeek-V4-Flash?

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

NVIDIA GPUs

AMD GPUs

Same job, different size

Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.

Next size down Qwen3 235B A22B 235B Next size up GLM-4.6 357B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does DeepSeek-V4-Flash need?

At Q4_K_M, DeepSeek-V4-Flash needs about 179.7 GB (weights ~174.87 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~307.1 GB.

What is the Q4_K_M GGUF file size of DeepSeek-V4-Flash?

The Q4_K_M GGUF file is about 174.87 GB to download, and the Q8_0 GGUF is about 302.27 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~179.7 GB of memory at Q4_K_M.

Can DeepSeek-V4-Flash run on a laptop?

DeepSeek-V4-Flash is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.

Is DeepSeek-V4-Flash cheaper to run because it is a MoE model?

It is faster, not lighter. DeepSeek-V4-Flash activates only 13B of 284B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 284B.

Can I use DeepSeek-V4-Flash commercially?

Yes. DeepSeek-V4-Flash is licensed MIT, which permits commercial use.

Understand the numbers

Short guides to the ideas behind DeepSeek-V4-Flash's memory and quant figures.

DeepSeek's efficient V4: 284B total, 13B active, 1M context, MIT. Q4_K_M and Q8_0 sums from split community GGUFs; bartowski's MXFP4 build is 156GB. The 1-bit floor (~62GB) fits a 96GB unified-memory machine, barely.

Sources

Last validated 2026-08-03. Memory figures are estimates. See methodology.