Can RTX 3090 Ti run Distil-Whisper Large v3?
Yes — runs locally
~132 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 3090 Ti (24 GB VRAM) handles Distil-Whisper Large v3 comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 132 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 3090 Ti
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Distil-Whisper Large v3 on an NVIDIA GeForce RTX 3090 Ti with Ollama using Q8_0 quantization for Grade S performance at ~746 tok/sec.
Prerequisites
Before starting, ensure you have at least 1.4GB of free disk space, a 64-bit version of Windows or Linux, and the latest NVIDIA drivers (version 525.60 or later) with CUDA 11.7 installed.
Expected performance
With the Q8_0 quantization, you can expect ~746 tok/sec performance, using 1.9GB of VRAM. The remaining 22.1GB of VRAM provides ample headroom for handling large context windows, making it suitable for long audio transcriptions.
1. Install runtimeOllama
curl -fsSL https://ollama.ai/install.sh | sh
ollama install2. 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:Q8_03. Run it
ollama run distil-whisper/distil-large-v3-ggml:Q8_0
ollama chat --model distil-whisper/distil-large-v3-ggml:Q8_04. Optimize for RTX 3090 Ti
For optimal performance on the NVIDIA GeForce RTX 3090 Ti with 24GB VRAM, set --n-gpu-layers to 48 to fully utilize the GPU. Enable flash attention (--flash-attn) to speed up inference. 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 the number of GPU layers by setting --n-gpu-layers to a lower value, such as 32.
Slow inference speed
Ensure that flash attention is enabled with --flash-attn and that the latest NVIDIA drivers and CUDA are installed.
Model not loading
Verify that the model file (ggml-distil-large-v3.bin) is correctly downloaded and not corrupted.
Alternative runtimes
Alternative runtimes include LM Studio and llama.cpp. LM Studio is useful for a more graphical interface and easier model management, while llama.cpp offers more customization options and is suitable for advanced users. For most users, Ollama provides a balanced combination of ease of use and performance on the NVIDIA GeForce RTX 3090 Ti.
Other models that run great on RTX 3090 Ti
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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