Can the NVIDIA RTX 3070 run Gemma 3 27B?

RTX 3070 × Gemma 3 27B8K context
NoDoes not fit in memory
Memory at Q4_K_M21.4 GB of 8 GB
Weights 16.6 GBKV cache 4.2 GBRuntime 0.6 GB
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

No. Even at Q4_K_M, Gemma 3 27B needs about 21.4 GB, but the NVIDIA RTX 3070 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

Run it on a rented GPU

On a cloud GPU with enough memory, the same command you'd use locally works:

ollama run gemma3:27b

At Q4_K_M it needs about 21.4 GB, so pick a GPU with at least 24 GB.

Run it in the cloud

Too big for the NVIDIA RTX 3070? Run Gemma 3 27B on a rented GPU instead.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 8 GB the NVIDIA RTX 3070 can use.

QuantQualityMemoryFits?Speed
FP16Full quality59.6 GBToo big—
Q8_0Near-lossless33.9 GBToo big—
Q6_KExcellent27.2 GBToo big—
Q5_K_MVery good24.2 GBToo big—
Q4_K_MGood, most popular21.4 GBToo big—
Q3_K_MNoticeably degraded18.2 GBToo big—
Q2_KHeavily degraded15 GBToo big—

Frequently asked questions

Can NVIDIA RTX 3070 run Gemma 3 27B?

No. Even at Q4_K_M, Gemma 3 27B needs about 21.4 GB, but the NVIDIA RTX 3070 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does Gemma 3 27B need?

About 21.4 GB at Q4_K_M with 8,192 tokens of context, and about 59.6 GB at full FP16 precision.

How fast is Gemma 3 27B on the NVIDIA RTX 3070?

It does not fit in the NVIDIA RTX 3070's memory, so most layers would run from system RAM and generation would be very slow.