Can RTX 3060 12GB run Whisper Medium?

Yes — runs locally

~84 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

12 GB

Model size

0.77B

Best quant

Q8_0

VRAM needed

1.9 GB

The verdict

The RTX 3060 12GB (12 GB VRAM) handles Whisper Medium comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 84 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Mid-size Whisper model. Strong multilingual speech recognition.

Setup tutorial: Whisper Medium on RTX 3060 12GB

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

TL;DR

Whisper Medium runs at Grade S (~371 tok/sec) on an NVIDIA GeForce RTX 3060 12GB using the Q8_0 quantization. This setup is highly optimized for fast speech recognition.

Prerequisites

Before starting, ensure you have at least 5GB of free disk space, a 64-bit version of Windows or Linux, NVIDIA driver version 470 or later, and CUDA 11.0 or later installed on your system.

Expected performance

With the Q8_0 quantization, you can expect Whisper Medium to run at approximately 371 tokens per second, using around 1.9GB of VRAM. This leaves you with 10.1GB of VRAM for context, enabling you to process longer audio segments without running out of memory.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q8_0 quantized version of Whisper Medium (1.4GB) from the Hugging Face repository.

ollama pull ggerganov/whisper.cpp:ggml-medium.bin

3. Run it

ollama run --model ggerganov/whisper.cpp:ggml-medium.bin --device cuda
ollama interactive

4. Optimize for RTX 3060 12GB

For optimal performance on the NVIDIA GeForce RTX 3060 12GB, set --n-gpu-layers to 32 to fully utilize the 12GB VRAM. Enable flash-attn for faster inference. Given the 1.9GB VRAM usage, you will have 10.1GB of VRAM left for context, allowing for a practical context window of several minutes of audio.

Troubleshooting

Out of memory error during inference

Reduce the number of --n-gpu-layers to 24 or 16 to lower VRAM usage.

Slow inference speed

Ensure that flash-attn is enabled and that your CUDA drivers are up to date.

Model fails to load

Verify that the model file was downloaded correctly and that the Ollama runtime is properly installed.

Alternative runtimes

For users who prefer different runtimes, consider LM Studio for a more user-friendly interface, llama.cpp for advanced customization options, or Jan for lightweight deployment. Each runtime has its own strengths, but Ollama provides a balanced approach for ease of use and performance on the NVIDIA GeForce RTX 3060 12GB.

Full Whisper Medium details →

Other models that run great on RTX 3060 12GB

FAQ (20)

What GPU do I need to run Whisper Medium?

To run Whisper Medium, you need a GPU with at least 1.9 GB of VRAM. NVIDIA GPUs such as the GTX 1060 or higher are recommended for optimal performance.

Is Whisper Medium good for coding?

Whisper Medium is primarily designed for speech recognition and is not optimized for coding tasks. For coding, models like Codex or CodeLlama are more suitable.

Whisper Medium vs Llama 3.1 8B?

Whisper Medium has 0.77 billion parameters and is specialized for speech recognition, while Llama 3.1 8B has 8 billion parameters and is a general-purpose language model. Llama 3.1 8B is better for text generation but requires more resources.

Can I run Whisper Medium on a Mac?

Yes, you can run Whisper Medium on a Mac. Ensure your Mac has a compatible GPU with at least 1.9 GB of VRAM and the necessary drivers installed.

How much VRAM does Whisper Medium need?

Whisper Medium requires at least 1.9 GB of VRAM to run efficiently. This can vary slightly depending on the quantization level used.

Is Whisper Medium censored?

Whisper Medium is not censored. It is an open-source model released under the MIT license, allowing for unrestricted use and modification.

Is Whisper Medium commercial-use allowed?

Yes, Whisper Medium is licensed under the MIT license, which allows for commercial use without any restrictions.

Whisper Medium context length?

The context length for Whisper Medium is not explicitly defined, but it is designed to handle typical speech segments effectively. For longer audio, you may need to split the input into smaller chunks.

Want personalized recommendations for your exact setup? Detect my hardware →