llamaperf

DeepSeek V4 Flash VRAM requirements

Memory needed to run DeepSeek V4 Flash at every published size and quant, with an 8k context. Each figure is weights plus KV cache plus runtime buffers, from the same memory model as the VRAM calculator.

Total memory by size and quant

GB at an 8k context. Bold is the Q4_K_M column, the usual starting point.

SizeQ8_0Q6_KQ5_K_MQ4_K_MQ3_K_M
9B119.48.37.26.0
284B · 13B active286233198162127
285B · 13B active287234198163127

KV cache by context length

GB the context alone adds on top of the weights. Add this to a weights figure to size a longer session.

SizeWeights at Q4_K_M4k ctx16k ctx32k ctx128k ctx
9B5.10.20.71.45.4
284B · 13B active1600.31.22.49.7
285B · 13B active1600.31.22.49.7

What each size fits on at Q4_K_M

Hardware whose memory holds the model with headroom, smallest pool first. Fits means under 85% of the pool at an 8k context.

Frequently asked

How much VRAM does DeepSeek V4 Flash need?

From about 7.2 GB for the 9B model to about 163 GB for the 285B · 13B active model, at Q4_K_M with an 8k context and including the KV cache and runtime buffers. Q8 needs more and Q3 less; the table above lists every size and rung.

Can I run DeepSeek V4 Flash on a 16GB GPU?

Yes. The 9B model needs about 7.2 GB at Q4_K_M with an 8k context, which fits a 16 GB card with headroom. Larger sizes need a smaller quant or a bigger card.

Can I run DeepSeek V4 Flash on a 24GB GPU such as an RTX 3090 or 4090?

Yes. The 9B model needs about 7.2 GB at Q4_K_M with an 8k context, which fits a 24 GB card with headroom. Larger sizes need a smaller quant or more memory.

How are these numbers calculated?

Weights at the quant's bits per weight, plus a KV cache sized from the model's attention design for the chosen context, plus compute buffers and a fixed runtime allowance. It is the same memory model the VRAM calculator uses. A family whose attention profile is not on file is sized as plain grouped-query attention, which errs towards needing more memory.