Gemma on NVIDIA Ampere

Can I run Gemma 3 27B on an RTX 3080 10GB?

Not at Q4_K_M — it needs 17.5 GB against 8.6 GB available. You would need 3 of these cards.

Won't fit

17.5 GB of 8.6 GB · 204%
018 GB
Weights 15.6 GB
KV cache 1.1 GB
Runtime overhead 0.8 GB
Over the limit 8.9 GB

Short by 8.9 GB. You can run it with 26 of 62 layers on the RTX 3080 10GB and the rest in system RAM, at roughly 3.97 tok/s — usable for batch work, painful for chat. A smaller quantisation or a shorter context is usually the better trade.

Generation3.97tok/s
Prompt processing460tok/s
Max context0tokens
KV per 1K tokens0GB

Every quantisation of Gemma 3 27B on a RTX 3080 10GB

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

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 51.0 GB 53.0 GB Won't fit 0.87
INT8 / W8A8 8.50 26.8 GB 28.7 GB Won't fit 1.86
Q8_0 (GGUF) 8.50 26.8 GB 28.7 GB Won't fit 1.86
FP8 (E4M3) 8.00 25.5 GB 27.4 GB Won't fit 1.99
Q6_K 6.56 20.9 GB 22.9 GB Won't fit 2.56
Q5_K_M 5.67 18.1 GB 20.0 GB Won't fit 3.14
Q5_K_S 5.52 17.6 GB 19.5 GB Won't fit 3.29
Q4_K_M 4.85 15.6 GB 17.5 GB Won't fit 3.97
AWQ 4-bit 4.25 15.5 GB 17.4 GB Won't fit 3.99
GPTQ 4-bit 4.25 15.5 GB 17.4 GB Won't fit 3.99
MXFP4 4.25 15.5 GB 17.4 GB Won't fit 3.99
Q4_K_S 4.58 14.8 GB 16.7 GB Won't fit 4.39
Q4_0 4.55 14.7 GB 16.6 GB Won't fit 4.41
IQ4_XS 4.25 13.8 GB 15.7 GB Won't fit 4.94
Q3_K_M 3.91 12.7 GB 14.7 GB Won't fit 5.61
IQ3_M 3.70 12.1 GB 14.0 GB Won't fit 6.24
IQ3_XXS 3.06 10.2 GB 12.1 GB Won't fit 8.93
Q2_K 2.63 8.9 GB 10.8 GB Won't fit 12.9
IQ2_XXS 2.06 7.1 GB 9.1 GB Won't fit 3K 31.7
IQ1_M 1.75 6.2 GB 8.1 GB Fits, but tight 14K 66.8

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