Can RTX 5090 run Distil-Whisper Large v3?
Yes — runs locally
~216 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 5090 (32 GB VRAM) handles Distil-Whisper Large v3 comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 216 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 5090
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Distil-Whisper Large v3 on an NVIDIA GeForce RTX 5090 with Ollama using Q8_0 quantization. Expect Grade S performance at ~995 tok/sec.
Prerequisites
Before starting, ensure you have at least 1.4GB of disk space available, a 64-bit version of Windows or Linux, and the latest NVIDIA drivers (version 525.60 or later) with CUDA 11.8 installed.
Expected performance
With the Q8_0 quantization, expect a throughput of approximately 995 tokens per second and 1.9GB of VRAM usage. This leaves 30.1GB of VRAM for context, allowing for a practical context window of several minutes of audio, depending on the specific requirements.
1. Install runtimeOllama
pip install ollama
ollama config set device cuda2. Download the model
Download the Q8_0 quantized version of Distil-Whisper Large v3 (1.4GB) from HuggingFace.
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 5090
For optimal performance on the NVIDIA GeForce RTX 5090 with 32GB VRAM, use the --n-gpu-layers flag to offload layers to the GPU. Set --n-gpu-layers to 32 to utilize the full VRAM capacity. Enable flash attention with --flash-attn to speed up inference. Consider using tensor parallelism with --tensor-parallel-size 2 to further enhance performance without exceeding the 32GB VRAM limit.
Troubleshooting
Out of memory error during inference
Reduce the number of GPU layers with --n-gpu-layers 16 or decrease the tensor parallelism with --tensor-parallel-size 1.
Slow inference speed
Ensure flash attention is enabled with --flash-attn and that the CUDA backend is properly configured.
Model not found error
Verify that the model was successfully downloaded with 'ollama list' and that the model name is correct.
Alternative runtimes
Consider using LM Studio for a more user-friendly interface, llama.cpp for fine-grained control over quantization and performance tuning, or Jan for lightweight deployment. Ollama is recommended for its ease of use and robust performance on the NVIDIA GeForce RTX 5090.
Other models that run great on RTX 5090
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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