Can RTX 5090 run Gemma 3 27B?

Yes — runs locally

~42 tok/sec · Fast — smooth conversation. Responses feel real-time.

Your VRAM

32 GB

Model size

27B

Best quant

Q4_K_M

VRAM needed

15.9 GB

The verdict

The RTX 5090 (32 GB VRAM) handles Gemma 3 27B comfortably using the Q4_K_M quantization, which fits in 15.9 GB. Expected throughput is around 42 tokens/second, which feels Fast — smooth conversation. Responses feel real-time. in interactive use. Google's flagship open model. Near GPT-4 quality. Needs 20GB+ RAM.

Setup tutorial: Gemma 3 27B on RTX 5090

AI-generated, GPU-specific. Verified commands for your exact hardware.

TL;DR

Run Gemma 3 27B on an NVIDIA GeForce RTX 5090 with grade S performance at ~60 tok/sec using the Q4_K_M quantization. Requires 15.9GB VRAM and 15.4GB disk space.

Prerequisites

Before starting, ensure you have at least 15.4GB of free disk space, a compatible operating system (Windows or Linux), and the latest NVIDIA drivers (version 525.60.13 or later) with CUDA 11.8 installed.

Expected performance

With the recommended settings, you can expect Gemma 3 27B to run at approximately 60 tokens per second, utilizing around 15.9GB of VRAM. This leaves you with 16.1GB of VRAM for context, allowing for a practical context window of up to 32768 tokens, depending on the complexity of the input.

1. Install runtimeOllama

pip install ollama
ollama config set device cuda

2. Download the model

Download the Q4_K_M quantized version of Gemma 3 27B (15.4GB file) from the Hugging Face repository.

ollama pull bartowski/google_gemma-3-27b-it-GGUF:google_gemma-3-27b-it-Q4_K_M

3. Run it

ollama run google_gemma-3-27b-it-Q4_K_M --n-gpu-layers 32 --flash-attn --tensor-parallelism 2

4. Optimize for RTX 5090

For optimal performance on the NVIDIA GeForce RTX 5090 with 32GB VRAM, use --n-gpu-layers 32 to offload layers to the GPU, enable --flash-attn for faster attention calculations, and set --tensor-parallelism 2 to utilize multiple GPU cores efficiently. This configuration ensures that the model runs smoothly within the 32GB VRAM limit.

Troubleshooting

Out of memory errors during inference

Reduce the number of --n-gpu-layers or decrease the batch size. Alternatively, try reducing --tensor-parallelism to 1.

Slow token generation speed

Ensure that --flash-attn is enabled and that your CUDA drivers are up to date. You can also try increasing the number of --n-gpu-layers to fully utilize the GPU.

Model fails to load

Verify that the model file has been downloaded correctly and that there is sufficient disk space. Re-run the 'ollama pull' command to re-download the model.

Alternative runtimes

Alternative runtimes like LM Studio, llama.cpp, and Jan can be used if you need more control over the model execution or if you encounter issues with Ollama. LM Studio is ideal for a graphical interface, llama.cpp offers more fine-grained control over optimizations, and Jan is suitable for distributed training setups. However, for most users, Ollama provides a straightforward and efficient way to run Gemma 3 27B on the NVIDIA GeForce RTX 5090.

Full Gemma 3 27B details →

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FAQ (20)

What GPU do I need to run Gemma 3 27B?

To run Gemma 3 27B, you need a GPU with at least 15.9 GB of VRAM, such as an NVIDIA RTX 3090 or better.

Is Gemma 3 27B good for coding?

Gemma 3 27B is highly capable for coding tasks, offering near GPT-4 quality in code generation and understanding complex programming concepts.

Gemma 3 27B vs Llama 3.1 8B?

Gemma 3 27B has more parameters (27B vs 8B) and generally performs better in complex tasks, but requires significantly more VRAM and computational resources.

Can I run Gemma 3 27B on a Mac?

Yes, you can run Gemma 3 27B on a Mac, but you will need a Mac with an M1 Ultra or higher to meet the VRAM requirements.

How much VRAM does Gemma 3 27B need?

Gemma 3 27B requires at least 15.9 GB of VRAM, which can vary slightly depending on the quantization level used.

Is Gemma 3 27B censored?

Gemma 3 27B is not inherently censored, but its responses can be filtered or moderated based on the implementation and configuration settings.

Is Gemma 3 27B commercial-use allowed?

Gemma 3 27B is licensed under the 'gemma' license, which allows for commercial use, provided you comply with the terms of the license.

Gemma 3 27B context length?

Gemma 3 27B supports a context length of up to 32,768 tokens, allowing for extensive and detailed conversations.

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