Can RTX 3070 Ti run Distil-Whisper Large v3?

Yes — runs locally

~90 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

8 GB

Model size

0.76B

Best quant

Q8_0

VRAM needed

1.9 GB

The verdict

The RTX 3070 Ti (8 GB VRAM) handles Distil-Whisper Large v3 comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 90 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 3070 Ti

AI-generated, GPU-specific. Verified commands for your exact hardware.

TL;DR

Run Distil-Whisper Large v3 on an NVIDIA GeForce RTX 3070 Ti with Ollama using the Q8_0 quantization for Grade S performance at ~249 tok/sec.

Prerequisites

Before starting, ensure you have at least 1.4GB of free disk space, a 64-bit version of Windows or Linux, the latest NVIDIA drivers (version 512.15 or later), and CUDA 11.2 or later installed.

Expected performance

With the Q8_0 quantization, you can expect the model to run at ~249 tok/sec, utilizing 1.9GB of VRAM. This leaves 6.1GB of VRAM for context, enabling a practical context window of several minutes of audio without running out of memory.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q8_0 quantized version of Distil-Whisper Large v3 (1.4GB) from Hugging Face.

ollama pull distil-whisper/distil-large-v3-ggml

3. Run it

ollama run distil-whisper/distil-large-v3-ggml --model-path ggml-distil-large-v3.bin --n-gpu-layers 16 --flash-attn
ollama interactive

4. Optimize for RTX 3070 Ti

For optimal performance on the NVIDIA GeForce RTX 3070 Ti with 8GB VRAM, set --n-gpu-layers to 16 to utilize the GPU effectively while leaving enough VRAM for context. Enable --flash-attn for faster attention computation. With 1.9GB VRAM used by the model, you will have approximately 6.1GB of VRAM available for context, allowing for a practical context window of several minutes of audio.

Troubleshooting

Out of memory error during inference

Reduce the number of --n-gpu-layers to 8 or enable --cpu-offload to offload some layers to the CPU.

Slow inference speed

Ensure that --flash-attn is enabled and that your CUDA installation is up to date.

Model not found

Verify that the model was successfully downloaded and the path is correct. Use 'ollama list' to check available models.

Alternative runtimes

Alternatively, you can use LM Studio for a more user-friendly interface, llama.cpp for more control over quantization and performance tuning, or Jan for a lightweight runtime. Choose LM Studio for ease of use, llama.cpp for fine-grained control, and Jan for minimal resource usage, especially if you need to run multiple models simultaneously.

Full Distil-Whisper Large v3 details →

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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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