Can the NVIDIA RTX 3090 run Gemma 4 31B?

RTX 3090 × Gemma 4 31B8K context
YesRuns fully on the GPU
Memory at Q4_K_M20.8 GB of 24 GB
Weights 19 GBKV cache 1.2 GBRuntime 0.6 GB
QuantQ4_K_MGood, most popular
Speed~30tokens per second
Max context84Ktokens that fit at Q4_K_M
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The NVIDIA RTX 3090 can run Gemma 4 31B fully in VRAM at Q4_K_M (good, most popular), using about 20.8 GB of the 24 GB available, at roughly 30 tokens/second.

Run it with Ollama

With Ollama installed, one command downloads and starts Gemma 4 31B:

ollama run gemma4:31b

Ollama's default download is Q4_K_M (about 20.8 GB here). That is also the best quant that fits.

New to this? Step-by-step setup for the RTX 3090

Run it in the cloud

No NVIDIA RTX 3090? Run Gemma 4 31B in the cloud.

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 24 GB the NVIDIA RTX 3090 can use.

QuantQualityMemoryFits?Speed
FP16Full quality64.4 GBToo big—
Q8_0Near-lossless35 GBToo big—
Q6_KExcellent27.4 GBToo big—
Q5_K_MVery good24 GBToo big—
Q4_K_MGood, most popular20.8 GBFits~30 tok/s
Q3_K_MNoticeably degraded17.1 GBFits~37 tok/s
Q2_KHeavily degraded13.5 GBFits~48 tok/s

Measured speed from real RTX 3090 owners

Tokens per second that people measured on their own NVIDIA RTX 3090, next to our estimate.

No one has measured Gemma 4 31B on the NVIDIA RTX 3090 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 3090? Add your real speed

One command times Gemma 4 31B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh -s -- gemma4:31b

Windows (PowerShell)

$env:GPUFIT_MODEL="gemma4:31b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

Frequently asked questions

Can NVIDIA RTX 3090 run Gemma 4 31B?

Yes. The NVIDIA RTX 3090 can run Gemma 4 31B fully in VRAM at Q4_K_M (good, most popular), using about 20.8 GB of the 24 GB available, at roughly 30 tokens/second.

How much VRAM does Gemma 4 31B need?

About 20.8 GB at Q4_K_M with 8,192 tokens of context, and about 64.4 GB at full FP16 precision.

How fast is Gemma 4 31B on the NVIDIA RTX 3090?

Roughly 30 tokens per second at Q4_K_M, estimated from the NVIDIA RTX 3090's 936 GB/s memory bandwidth.