Can RTX 4060 run Whisper Large v3 Turbo?
Yes — runs locally
~102 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4060 (8 GB VRAM) handles Whisper Large v3 Turbo comfortably using the Q8_0 quantization, which fits in 2.0 GB. Expected throughput is around 102 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
AI-generated, GPU-specific. Verified commands for your exact hardware.
Whisper Large v3 Turbo runs at Grade S on the NVIDIA GeForce RTX 4060 with Q8_0 quantization, achieving ~238 tok/sec.
Prerequisites
Before starting, ensure you have at least 1.5GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 525.60.13 or later), and CUDA 11.8 installed.
Expected performance
With the recommended settings, you can expect the model to run at approximately 238 tokens per second, using 2.0GB of VRAM. The remaining 6.0GB of VRAM provides ample headroom for handling longer audio contexts, enabling efficient processing of extended audio clips.
1. Install runtimeOllama
pip install ollama
ollama init2. Download the model
Download the Q8_0 quantized model (1.5GB) from the Hugging Face repository.
ollama pull ggerganov/whisper.cpp:ggml-large-v3-turbo.bin3. Run it
ollama run ggerganov/whisper.cpp:ggml-large-v3-turbo.bin --device cuda
ollama interactive4. Optimize for RTX 4060
For optimal performance on the NVIDIA GeForce RTX 4060 with 8GB VRAM, use the --n-gpu-layers flag to specify the number of layers to offload to the GPU. Set --n-gpu-layers to 24 to balance between speed and memory usage. Enable flash attention (--flash-attn) to further optimize inference. With 2.0GB VRAM used by the model, you will have 6.0GB of VRAM available for context, allowing for a practical context window of several minutes of audio.
Troubleshooting
CUDA out of memory error
Reduce the number of GPU layers with --n-gpu-layers 16 or lower.
Slow inference speed
Ensure flash attention is enabled with --flash-attn and check your CUDA installation.
Model not found
Verify the model path and ensure the model is correctly downloaded with ollama pull.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio is suitable for users who prefer a graphical interface. llama.cpp offers more control over model parameters and is ideal for advanced users. Jan is a lightweight runtime that is easy to set up but may not offer the same level of performance tuning as Ollama. For the NVIDIA GeForce RTX 4060, Ollama is recommended for its ease of use and robust performance.
Other models that run great on RTX 4060
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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