Gemma on NVIDIA Ada

Can I run Gemma 3 27B on an RTX 4070 Ti Super?

Not at Q4_K_M — it needs 17.5 GB against 14.2 GB available. Drop to IQ3_M and it fits, at about 31.0 tokens per second.

Won't fit

17.5 GB of 14.2 GB · 123%
018 GB
Weights 15.6 GB
KV cache 1.1 GB
Runtime overhead 0.8 GB
Over the limit 3.3 GB

Short by 3.3 GB. You can run it with 48 of 62 layers on the RTX 4070 Ti Super and the rest in system RAM, at roughly 7.81 tok/s — usable for batch work, painful for chat. A smaller quantisation or a shorter context is usually the better trade.

Generation7.81tok/s
Prompt processing674tok/s
Max context0tokens
KV per 1K tokens0GB

Every quantisation of Gemma 3 27B on a RTX 4070 Ti Super

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 0.93
INT8 / W8A8 8.50 26.8 GB 28.7 GB Won't fit 2.35
Q8_0 (GGUF) 8.50 26.8 GB 28.7 GB Won't fit 2.35
FP8 (E4M3) 8.00 25.5 GB 27.4 GB Won't fit 2.53
Q6_K 6.56 20.9 GB 22.9 GB Won't fit 3.72
Q5_K_M 5.67 18.1 GB 20.0 GB Won't fit 5.24
Q5_K_S 5.52 17.6 GB 19.5 GB Won't fit 5.59
Q4_K_M 4.85 15.6 GB 17.5 GB Won't fit 7.81
AWQ 4-bit 4.25 15.5 GB 17.4 GB Won't fit 8.26
GPTQ 4-bit 4.25 15.5 GB 17.4 GB Won't fit 8.26
MXFP4 4.25 15.5 GB 17.4 GB Won't fit 8.26
Q4_K_S 4.58 14.8 GB 16.7 GB Won't fit 9.63
Q4_0 4.55 14.7 GB 16.6 GB Won't fit 10.3
IQ4_XS 4.25 13.8 GB 15.7 GB Won't fit 13.3
Q3_K_M 3.91 12.7 GB 14.7 GB Won't fit 3K 20.3
IQ3_M 3.70 12.1 GB 14.0 GB Fits, but tight 10K 31.0
IQ3_XXS 3.06 10.2 GB 12.1 GB Runs comfortably 33K 36.5
Q2_K 2.63 8.9 GB 10.8 GB Runs comfortably 48K 41.3
IQ2_XXS 2.06 7.1 GB 9.1 GB Runs comfortably 68K 50.2
IQ1_M 1.75 6.2 GB 8.1 GB Runs comfortably 79K 56.8

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