Can RTX 4060 Ti run Whisper Large v3 Turbo?

Yes — runs locally

~114 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

8 GB

Model size

0.81B

Best quant

Q8_0

VRAM needed

2.0 GB

The verdict

The RTX 4060 Ti (8 GB VRAM) handles Whisper Large v3 Turbo comfortably using the Q8_0 quantization, which fits in 2.0 GB. Expected throughput is around 114 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Optimized large Whisper model. Near-best accuracy with faster inference.

Setup tutorial: Whisper Large v3 Turbo on RTX 4060 Ti

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

TL;DR

Whisper Large v3 Turbo runs at Grade S on the NVIDIA GeForce RTX 4060 Ti with Q8_0 quantization, achieving ~238 tok/sec.

Prerequisites

Before starting, ensure you have at least 1.5GB of free disk space, a 64-bit version of Windows or Linux, and the latest NVIDIA drivers (version 525.60.12 or later) with CUDA 11.7 or later installed.

Expected performance

With the recommended settings, you can expect Whisper Large v3 Turbo to run at ~238 tok/sec, using approximately 2.0GB of VRAM. This leaves 6.0GB of VRAM for context, allowing for a practical context window of several minutes of audio depending on the audio quality and sampling rate.

1. Install runtimeOllama

curl -fsSL https://ollama.com/install.sh | sh
ollama config set device cuda

2. Download the model

Download the Q8_0 quantized version of Whisper Large v3 Turbo (1.5GB file) from Hugging Face.

ollama pull ggerganov/whisper.cpp:ggml-large-v3-turbo.bin

3. Run it

ollama run ggerganov/whisper.cpp:ggml-large-v3-turbo.bin --device cuda --n-gpu-layers 128 --flash-attn

4. Optimize for RTX 4060 Ti

For optimal performance on the NVIDIA GeForce RTX 4060 Ti with 8GB VRAM, use the --n-gpu-layers 128 flag to offload some layers to the CPU, enabling flash attention (--flash-attn) for faster inference. This configuration will help you achieve the target ~238 tok/sec while keeping VRAM usage around 2.0GB, leaving 6.0GB for context.

Troubleshooting

Error: CUDA out of memory

Reduce the number of GPU layers with --n-gpu-layers 64 or lower, and ensure that your system has enough CPU RAM to handle the offloaded layers.

Low tokenization speed

Ensure that the --flash-attn flag is enabled to leverage optimized attention mechanisms for faster inference.

Model not found

Verify that the model was correctly downloaded and is available in the Ollama model directory. Use 'ollama list' to check.

Alternative runtimes

For users who prefer different runtimes, consider LM Studio for a more graphical interface, llama.cpp for fine-grained control over quantization and performance tuning, or Jan for a lightweight, easy-to-use alternative. Choose based on your specific needs for GUI, customization, or simplicity.

Full Whisper Large v3 Turbo details →

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FAQ (20)

What GPU do I need to run Whisper Large v3 Turbo?

To run Whisper Large v3 Turbo, you need a GPU with at least 2.0 GB of VRAM. The exact VRAM requirement can vary slightly depending on the quantization level used.

Is Whisper Large v3 Turbo good for coding?

Whisper Large v3 Turbo is primarily designed for speech recognition tasks and may not be optimized for coding-related tasks. For coding, models like Codex or CodeLLaMa might be more suitable.

Whisper Large v3 Turbo vs Llama 3.1 8B?

Whisper Large v3 Turbo has 0.81 billion parameters and is optimized for speech recognition, while Llama 3.1 8B has 8 billion parameters and is more versatile for general language tasks. Choose based on your specific needs.

Can I run Whisper Large v3 Turbo on a Mac?

Yes, you can run Whisper Large v3 Turbo on a Mac as long as your Mac has a compatible GPU with at least 2.0 GB of VRAM. Ensure you have the necessary drivers and libraries installed.

How much VRAM does Whisper Large v3 Turbo need?

Whisper Large v3 Turbo requires at least 2.0 GB of VRAM. The exact amount can vary slightly depending on the quantization level used.

Is Whisper Large v3 Turbo censored?

Whisper Large v3 Turbo is not censored. It is an open-source model released under the MIT license, allowing for broad usage without content restrictions.

Is Whisper Large v3 Turbo commercial-use allowed?

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

Whisper Large v3 Turbo context length?

The context length for Whisper Large v3 Turbo is currently unknown. Refer to the official documentation or model repository for the most accurate information.

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