DeepSeek on NVIDIA Ada

Can I run DeepSeek-R1 671B-A37B on an RTX 4090?

Not at Q4_K_M — it needs 380.4 GB against 21.8 GB available. No quantisation of this model fits on one card.

Won't fit

380.4 GB of 21.8 GB · 1748%
0396 GB
Weights 379.0 GB
KV cache 0.5 GB
Runtime overhead 0.9 GB
Over the limit 358.6 GB

Short by 358.6 GB. You can run it with 3 of 61 layers on the RTX 4090 and the rest in system RAM, at roughly 1.88 tok/s — usable for batch work, painful for chat. A smaller quantisation or a shorter context is usually the better trade.

Generation1.88tok/s
Prompt processing936tok/s
Max context0tokens
KV per 1K tokens0GB

Every quantisation of DeepSeek-R1 671B-A37B on a RTX 4090

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 1249.8 GB 1251.2 GB Won't fit 0.55
INT8 / W8A8 8.50 663.6 GB 665.0 GB Won't fit 1.05
Q8_0 (GGUF) 8.50 663.6 GB 665.0 GB Won't fit 1.05
FP8 (E4M3) 8.00 624.9 GB 626.3 GB Won't fit 1.11
Q6_K 6.56 512.4 GB 513.8 GB Won't fit 1.37
Q5_K_M 5.67 442.9 GB 444.3 GB Won't fit 1.59
Q5_K_S 5.52 431.2 GB 432.6 GB Won't fit 1.63
Q4_K_M 4.85 379.0 GB 380.4 GB Won't fit 1.88
Q4_K_S 4.58 358.0 GB 359.4 GB Won't fit 1.98
Q4_0 4.55 355.6 GB 357.0 GB Won't fit 2.00
AWQ 4-bit 4.25 334.5 GB 335.9 GB Won't fit 2.12
GPTQ 4-bit 4.25 334.5 GB 335.9 GB Won't fit 2.12
MXFP4 4.25 334.5 GB 335.9 GB Won't fit 2.12
IQ4_XS 4.25 332.3 GB 333.7 GB Won't fit 2.13
Q3_K_M 3.91 305.8 GB 307.2 GB Won't fit 2.35
IQ3_M 3.70 289.4 GB 290.8 GB Won't fit 2.48
IQ3_XXS 3.06 239.6 GB 241.0 GB Won't fit 3.03
Q2_K 2.63 206.1 GB 207.5 GB Won't fit 3.55
IQ2_XXS 2.06 161.7 GB 163.1 GB Won't fit 4.55
IQ1_M 1.75 137.5 GB 138.9 GB Won't fit 5.49

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