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Text model · DeepSeek-V3

DeepSeek V3: RAM and VRAM requirements

DeepSeek V3 needs about 383.7 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~376.65 GB to download; KV cache and overhead add the rest), or about 671.3 GB at Q8_0. The lightest hardware that runs it is a high-memory machine.

DeepSeek-V3 family · 671B params (Mixture-of-Experts: activates only 37B of 671B params per token, so generation is faster than the total size suggests) · released Mar 2025.

Shopping for hardware? See what runs DeepSeek V3 →

License MIT · Commercial OK ↓ 899.2K/mo ♥ 3.2K on HuggingFace
Q4_K_M GGUF
376.65 GB
Q8_0 GGUF
664.3 GB
Memory @ Q4 (4k)
~383.7 GB
Context
128 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 V3 runs on 0 of 40 tracked devices at Q4_K_M.

0 run well 0 tight fit 40 too small
Fit check Q4_K_M
No, not enough memory
needs 383.7 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)376.65 GB
+
KV cache (4k)6.2 GB
+
Overhead0.8 GB
=
Total383.7 GB

How context length changes it

4k context ~383.7 GB 32k context ~427.2 GB 128k context ~576.3 GB

Longer context grows the KV cache, which for DeepSeek V3 is sized by its 37B active params, not the full 671B. It needs ~383.7 GB at 4k and ~576.3 GB at 128k.

Benchmark scores

Aider polyglot · coding

#5 of 10 ranked · Percent of 225 Exercism exercises solved across six languages.

55.1%

Sourced third-party benchmarks for the full-precision DeepSeek V3, not a specific quant. See the full leaderboard.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 281 GB est
Q3_K_M 328 GB est
Q4_K_M (default) 376.65 GB
Q5_K_M 478.1 GB est
Q6_K 550.2 GB est
Q8_0 664.3 GB
FP16 1342 GB est

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

Run it

Ollama
$ ollama run deepseek-v3:671b
llama.cpp
$ llama-cli -hf unsloth/DeepSeek-V3-0324-GGUF:Q4_K_M
LM Studio
$ lms get unsloth/DeepSeek-V3-0324-GGUF

Which devices can run DeepSeek V3?

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 Nemotron 3 Ultra 550B-A55B 550B Next size up GLM-5.2 744B

Similar models

FAQ

How much VRAM or RAM does DeepSeek V3 need?

At Q4_K_M, DeepSeek V3 needs about 383.7 GB (weights ~376.65 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~671.3 GB.

What is the Q4_K_M GGUF file size of DeepSeek V3?

The Q4_K_M GGUF file is about 376.65 GB to download, and the Q8_0 GGUF is about 664.3 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~383.7 GB of memory at Q4_K_M.

Can DeepSeek V3 run on a laptop?

DeepSeek V3 is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.

Is DeepSeek V3 cheaper to run because it is a MoE model?

It is faster, not lighter. DeepSeek V3 activates only 37B of 671B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 671B.

Can I use DeepSeek V3 commercially?

Yes. DeepSeek V3 is licensed MIT, which permits commercial use.

Understand the numbers

Short guides to the ideas behind DeepSeek V3's memory and quant figures.

DeepSeek V3 (0324 build), 671B sparse MoE (37B active). Q4_K_M is ~377GB across a 9-file series. Low-bit dynamic quants fit ~150GB. Size from the unsloth GGUF repo.

Sources

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