Can the NVIDIA RTX 4060 run Gemma 2 27B?

RTX 4060 × Gemma 2 27B8K context
NoDoes not fit in memory
Memory at Q4_K_M20.2 GB of 8 GB
Weights 16.5 GBKV cache 3.1 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 2 27B needs about 20.2 GB, but the NVIDIA RTX 4060 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 gemma2:27b

At Q4_K_M it needs about 20.2 GB, so pick a GPU with at least 24 GB.

Run it in the cloud

Too big for the NVIDIA RTX 4060? Run Gemma 2 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 4060 can use.

QuantQualityMemoryFits?Speed
FP16Full quality58.1 GBToo big—
Q8_0Near-lossless32.6 GBToo big—
Q6_KExcellent26 GBToo big—
Q5_K_MVery good23 GBToo big—
Q4_K_MGood, most popular20.2 GBToo big—
Q3_K_MNoticeably degraded17 GBToo big—
Q2_KHeavily degraded13.9 GBToo big—

Frequently asked questions

Can NVIDIA RTX 4060 run Gemma 2 27B?

No. Even at Q4_K_M, Gemma 2 27B needs about 20.2 GB, but the NVIDIA RTX 4060 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does Gemma 2 27B need?

About 20.2 GB at Q4_K_M with 8,192 tokens of context, and about 58.1 GB at full FP16 precision.

How fast is Gemma 2 27B on the NVIDIA RTX 4060?

It does not fit in the NVIDIA RTX 4060's memory, so most layers would run from system RAM and generation would be very slow.