Can RTX 3060 12GB run Whisper Large v3 Turbo?
Yes — runs locally
~84 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 3060 12GB (12 GB VRAM) handles Whisper Large v3 Turbo comfortably using the Q8_0 quantization, which fits in 2.0 GB. Expected throughput is around 84 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 3060 12GB
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Whisper Large v3 Turbo on an NVIDIA GeForce RTX 3060 12GB with Ollama. Grade S performance, using Q8_0 quantization, expect ~356 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 510.73 or later), and CUDA 11.2 or later installed.
Expected performance
With the recommended settings, you can expect ~356 tok/sec performance, using approximately 2.0GB of VRAM. This leaves 10.0GB of VRAM for context, enabling a practical context window of several minutes of audio without running out of memory.
1. Install runtimeOllama
curl -sSL https://ollama.ai/install.sh | sh
ollama install2. 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-turbo3. Run it
ollama run ggerganov/whisper.cpp:ggml-large-v3-turbo --device cuda
ollama interactive ggerganov/whisper.cpp:ggml-large-v3-turbo4. Optimize for RTX 3060 12GB
For optimal performance on the NVIDIA GeForce RTX 3060 12GB, set --n-gpu-layers to 32 to utilize the 12GB VRAM efficiently. Enable flash-attn for faster inference. Given the 12GB VRAM, you can allocate up to 10GB for context, allowing for a practical context window of several minutes of audio.
Troubleshooting
Out of memory errors during inference
Reduce the --n-gpu-layers value to 24 or lower to free up more VRAM for context.
Slow inference speed
Ensure that flash-attn is enabled and that your CUDA drivers are up to date.
Model fails to load
Verify that the model file is correctly downloaded and not corrupted. Try re-downloading the model using the 'ollama pull' command.
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 a lightweight option for those who need minimal dependencies. Jan is a good choice for advanced users who require fine-grained control over the inference process. For the NVIDIA GeForce RTX 3060 12GB, Ollama provides the best balance of ease of use and performance.
Other models that run great on RTX 3060 12GB
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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