Model requirements

Gemma 2 9B GPU Requirements

Gemma 2 9B usually starts around 6-8 GB in INT4, 10-12 GB in INT8, and 18-20 GB in FP16. A safe production starting point is RTX 4090 24GB or A10G 24GB.

Price Gemma 2 9BEstimate cost
INT4 start
6-8 GB
Approximate starting range before runtime headroom.
FP16 start
18-20 GB
Useful for accuracy-first deployments.
Safe GPU floor
RTX 4090 24GB or A10G 24GB
A strong default when you want one safe answer fast.

VRAM table

Gemma 2 9B memory and route profile

Gemma 2 9B is primarily used for compact open-model inference with strong quality per dollar. Most teams start with the quickest safe answer for memory fit, then compare which production routes make sense.

Use these ranges as practical planning estimates. Your actual requirements still depend on runtime overhead, batching, and the execution framework.

PrecisionApproximate VRAMTypical route
INT46-8 GBCheapest healthy route when quality holds
INT810-12 GBBalanced production starting point
FP1618-20 GBAccuracy-first route with more headroom

Execution notes

What changes the route in production

A memory-fit answer is only useful if the route is healthy. Pages like this should explain that fit, latency, and route quality all matter once the model goes live.

For Gemma 2 9B, the most relevant follow-up pages are the cost page and the run-without-GPU page because those are the next practical questions most teams ask.

  • Compact production assistants
  • Retrieval-augmented apps
  • Cost-aware open-model deployments

Next step

Take Gemma 2 9B from research into a real route

Once the fit is clear, price the route and test one workload so you can compare the theory against live capacity.

Open the estimatorRun this workload
CostCost to run Gemma 2 9BCheck the operating range and what changes the bill in production.DocsDocs and execution workflowInspect the API, CLI, and portal paths if you want to run the model immediately.

FAQ

Frequently asked

What GPU do I need for Gemma 2 9B?

A safe starting answer is RTX 4090 24GB or A10G 24GB. Lighter quantized routes can use less memory, but that is the clean default most teams need first.

Can Gemma 2 9B run on a consumer GPU?

In many cases yes, especially with quantization. The safer answer still depends on the exact precision, runtime overhead, and traffic shape you expect in production.

How can I estimate the cost of running Gemma 2 9B remotely?

Use the pricing estimator after reviewing the requirements. It can help you compare a remote route with buying or managing hardware directly.