Can RTX 4090 run Whisper Large v3 Turbo?
Yes — runs locally
~192 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4090 (24 GB VRAM) handles Whisper Large v3 Turbo comfortably using the Q8_0 quantization, which fits in 2.0 GB. Expected throughput is around 192 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 4090
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Whisper Large v3 Turbo on an NVIDIA GeForce RTX 4090 with Q8_0 quantization for Grade S performance at ~713 tok/sec.
Prerequisites
Before starting, ensure you have at least 1.5GB of free disk space, a compatible OS (Windows or Linux), the latest NVIDIA drivers (version 525.60.13 or later), and CUDA 11.8 installed.
Expected performance
With the Q8_0 quantization, you can expect ~713 tok/sec performance, utilizing 2.0GB of VRAM. The remaining 22.0GB of VRAM provides ample headroom for handling large context windows, enabling the processing of extended audio clips without performance degradation.
1. Install runtimeOllama
sudo apt-get update && sudo apt-get install -y ollama
ollama init2. 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.bin3. Run it
ollama run ggerganov/whisper.cpp:ggml-large-v3-turbo.bin --model-path ggml-large-v3-turbo.bin
ollama chat ggerganov/whisper.cpp:ggml-large-v3-turbo.bin4. Optimize for RTX 4090
For optimal performance on the NVIDIA GeForce RTX 4090 with 24GB VRAM, set --n-gpu-layers to 64 to fully utilize the GPU. Enable flash-attn for faster inference and consider using tensor parallelism if you need to handle larger context windows. With 2.0GB VRAM used by the model, you have 22.0GB of VRAM available for context, allowing for very long audio inputs.
Troubleshooting
Low token throughput
Ensure that flash-attn is enabled and --n-gpu-layers is set to 64. If the issue persists, check your CUDA installation and driver versions.
Out of memory errors
Reduce the number of --n-gpu-layers or decrease the context window size to fit within the available 22.0GB VRAM.
Model not found
Verify that the model has been successfully downloaded and is located in the correct directory. Use 'ollama list' to check available models.
Alternative runtimes
Alternative runtimes like LM Studio, llama.cpp, and Jan can be used if you need more customization options or specific features not available in Ollama. For example, llama.cpp offers more control over quantization and optimization settings, which might be useful for fine-tuning performance on the RTX 4090.
Other models that run great on RTX 4090
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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