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DeepSeek V4 Flash

MoE

DeepSeekDeepSeek · 290.9B (13B active) · Mixture of experts

DeepSeek V4 Flash is a 290.9B model from DeepSeek with a 1M-token context. At Q4_K_M with an 8K context it needs about 166.7 GB; 210 GB leaves room for longer chats.

Hugging Face GGUF

Mixture of experts

Parameters: 290.9B · Active: 13B

All 290.9B parameters load into memory, but only 13B work on each token, so it runs at the speed of a much smaller model.

Quantization options

QuantMemoryOn your hardware
Q2_K—…
Q3_K_M—…
Q4_K_M—…
Q5_K_M—…
Q6_K—…
Q8_0—…
F16—…

Memory by context length

At Q4_K_M. The context cache grows with every token the model keeps in mind.

ContextContext cacheTotal
4K0.3 GB166.4 GB
8K0.7 GB166.7 GB
32K2.7 GB168.8 GB
128K10.8 GB176.8 GB
256K21.5 GB187.6 GB

Share a measured speed

Run one of these and paste the whole output below (or just the tokens per second):

llama-bench -m model.gguf
ollama run model --verbose

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Next steps

Least hardware that runs it well

Desktop devices with the least memory that give DeepSeek V4 Flash grade A or S at Q4_K_M.

Can I run DeepSeek V4 Flash locally?

Can I run DeepSeek V4 Flash locally?

Yes, if your GPU or Mac has about 166.7 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.

How much memory does DeepSeek V4 Flash need?

About 166.7 GB at Q4_K_M with an 8K context and 288.9 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.