Can RTX 4080 SUPER run Whisper Medium?

Yes — runs locally

~156 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

16 GB

Model size

0.77B

Best quant

Q8_0

VRAM needed

1.9 GB

The verdict

The RTX 4080 SUPER (16 GB VRAM) handles Whisper Medium comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 156 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 4080 SUPER

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

TL;DR

Run Whisper Medium on an NVIDIA GeForce RTX 4080 SUPER with Q8_0 quantization for Grade S performance at ~495 tok/sec.

Prerequisites

Before starting, ensure you have at least 1.4GB 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, expect ~495 tok/sec performance and 1.9GB VRAM usage, leaving 14.1GB of VRAM available for context. This allows for a practical context window of several minutes of audio, depending on the resolution and sampling rate.

1. Install runtimeOllama

pip install ollama
ollama config set device cuda

2. Download the model

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

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

3. Run it

ollama run ggerganov/whisper.cpp:ggml-medium.bin --model-quantization Q8_0 --device cuda
ollama interactive ggerganov/whisper.cpp:ggml-medium.bin

4. Optimize for RTX 4080 SUPER

For optimal performance on the NVIDIA GeForce RTX 4080 SUPER with 16GB VRAM, set --n-gpu-layers to 32 to fully utilize the GPU. Enable flash attention (--flash-attn) to speed up inference. With 1.9GB VRAM used by the model, you have 14.1GB of VRAM left for context, allowing for a large practical context window.

Troubleshooting

Inference is slow or uses excessive CPU

Ensure CUDA is properly installed and the device is set to cuda using 'ollama config set device cuda'.

Out of memory errors during inference

Reduce the number of GPU layers using '--n-gpu-layers <number>' to fit within the available VRAM.

Model does not load

Verify the model file is correctly downloaded and not corrupted. Try re-downloading the model using 'ollama pull ggerganov/whisper.cpp:ggml-medium.bin'.

Alternative runtimes

Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio is suitable for a more user-friendly interface, llama.cpp offers advanced customization options, and Jan is ideal for lightweight, low-resource environments. However, Ollama provides a balanced approach with good performance and ease of use, making it the recommended choice for the NVIDIA GeForce RTX 4080 SUPER.

Full Whisper Medium details →

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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.

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