Can RTX 4090 run Distil-Whisper Large v3?

Yes — runs locally

~192 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

24 GB

Model size

0.76B

Best quant

Q8_0

VRAM needed

1.9 GB

The verdict

The RTX 4090 (24 GB VRAM) handles Distil-Whisper Large v3 comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 192 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Distilled Whisper. 6x faster than large-v3 with 1% accuracy loss.

Setup tutorial: Distil-Whisper Large v3 on RTX 4090

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

TL;DR

Run Distil-Whisper Large v3 on an NVIDIA GeForce RTX 4090 with grade S performance, using the Q8_0 quantization for ~746 tok/sec.

Prerequisites

Before starting, ensure you have at least 1.5GB of free disk space, a compatible OS (Windows 10/11 or Linux), and the latest NVIDIA drivers (version 525.60.13 or later) with CUDA 11.8 installed.

Expected performance

With the Q8_0 quantization, you can expect ~746 tok/sec performance and 1.9GB VRAM usage. The remaining 22.1GB of VRAM provides ample headroom for handling long context windows, making it suitable for extended speech processing tasks.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q8_0 quantized version of Distil-Whisper Large v3 (1.4GB file) from the Hugging Face repository.

ollama pull distil-whisper/distil-large-v3-ggml

3. Run it

ollama run distil-whisper/distil-large-v3-ggml --n-gpu-layers 48 --flash-attn
ollama interactive distil-whisper/distil-large-v3-ggml

4. Optimize for RTX 4090

For optimal performance on the NVIDIA GeForce RTX 4090 with 24GB VRAM, set --n-gpu-layers to 48 to fully utilize the GPU. Enable --flash-attn for faster attention computation. With 1.9GB VRAM used by the model, you have 22.1GB of VRAM left for context, allowing for a large practical context window.

Troubleshooting

Out of memory error during inference

Reduce --n-gpu-layers to 32 or 24 to lower VRAM usage.

Low token generation speed

Ensure --flash-attn is enabled and check that your CUDA installation is up to date.

Model not loading

Verify the model file integrity and re-download if necessary using 'ollama pull distil-whisper/distil-large-v3-ggml'.

Alternative runtimes

Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio offers a graphical interface and is suitable for users who prefer a GUI. llama.cpp is highly customizable and can be used for more advanced tuning options. Jan is lightweight and ideal for quick prototyping. However, Ollama provides a balanced combination of ease of use and performance, making it the recommended choice for this setup.

Full Distil-Whisper Large v3 details →

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FAQ (20)

What GPU do I need to run Distil-Whisper Large v3?

To run Distil-Whisper Large v3, you need a GPU with at least 1.9 GB of VRAM. NVIDIA GPUs such as the GTX 1060 or higher are recommended.

Is Distil-Whisper Large v3 good for coding?

Distil-Whisper Large v3 is primarily designed for speech recognition tasks and may not be optimized for coding-specific tasks. For coding, models like Codex or CodeLlama are more suitable.

Distil-Whisper Large v3 vs Llama 3.1 8B?

Distil-Whisper Large v3 has 0.76B parameters and is optimized for speech recognition, while Llama 3.1 8B is a larger, more versatile model with 8B parameters, better suited for a wider range of NLP tasks.

Can I run Distil-Whisper Large v3 on a Mac?

Yes, you can run Distil-Whisper Large v3 on a Mac, but ensure your Mac has a compatible GPU with at least 1.9 GB of VRAM. M1 and later Macs with Metal support are recommended.

How much VRAM does Distil-Whisper Large v3 need?

Distil-Whisper Large v3 requires 1.9 GB of VRAM, which is consistent across different quantization levels.

Is Distil-Whisper Large v3 censored?

No, Distil-Whisper Large v3 is not censored. It is an open-source model under the MIT license, allowing for unrestricted use and modification.

Is Distil-Whisper Large v3 commercial-use allowed?

Yes, Distil-Whisper Large v3 is licensed under the MIT license, which allows for commercial use without restrictions.

Distil-Whisper Large v3 context length?

The context length for Distil-Whisper Large v3 is currently unknown. For more detailed information, refer to the model's documentation or source code.

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