Can RTX 5060 Ti run Whisper Medium?
Yes — runs locally
~156 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 5060 Ti (16 GB VRAM) handles Whisper Medium comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 156 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Mid-size Whisper model. Strong multilingual speech recognition.
Setup tutorial: Whisper Medium on RTX 5060 Ti
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Whisper Medium on an NVIDIA GeForce RTX 5060 Ti with Ollama using the Q8_0 quantization. Expect Grade S performance at ~495 tok/sec.
Prerequisites
Before starting, ensure you have at least 1.4GB of disk space, a compatible operating system (Windows or Linux), and the latest NVIDIA drivers (version 525.60.13 or later) with CUDA 11.8 installed.
Expected performance
With the recommended settings, you can expect ~495 tok/sec performance, utilizing approximately 1.9GB of VRAM. This leaves 14.1GB of VRAM available for context, allowing for a practical context window of several minutes of audio depending on the resolution and sampling rate.
1. Install runtimeOllama
curl -fsSL https://ollama.com/install.sh | sh
ollama init2. Download the model
Download the Q8_0 quantized version of Whisper Medium from Hugging Face (1.4GB file).
ollama pull ggerganov/whisper.cpp:ggml-medium.bin3. Run it
ollama run ggerganov/whisper.cpp:ggml-medium.bin --model-kwargs="{'use_flash_attention': True, 'tensor_parallel': 1}"4. Optimize for RTX 5060 Ti
For optimal performance on the NVIDIA GeForce RTX 5060 Ti with 16GB VRAM, set --n-gpu-layers to 32 to utilize the GPU effectively. Enable flash attention (--use-flash-attention) to speed up inference, and set tensor parallelism to 1 for single-GPU operation. This configuration will maximize the ~495 tok/sec throughput while keeping VRAM usage efficient.
Troubleshooting
Inference is slow or hangs.
Ensure that flash attention is enabled and that the correct number of GPU layers is set. Try reducing --n-gpu-layers if necessary.
Out of memory errors.
Reduce the number of --n-gpu-layers or decrease the batch size if applicable.
Model fails to load.
Verify that the model file has been downloaded correctly and that the Ollama runtime is properly installed and initialized.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. Use LM Studio for a more user-friendly interface, llama.cpp for advanced customization, and Jan for cloud-based deployment. However, Ollama provides a balanced approach with ease of use and performance optimization for the NVIDIA GeForce RTX 5060 Ti.
Other models that run great on RTX 5060 Ti
FAQ (20)
What GPU do I need to run Whisper Medium?
To run Whisper Medium, you need a GPU with at least 1.9 GB of VRAM. NVIDIA GPUs such as the GTX 1060 or higher are recommended for optimal performance.
Is Whisper Medium good for coding?
Whisper Medium is primarily designed for speech recognition and is not optimized for coding tasks. For coding, models like Codex or CodeLlama are more suitable.
Whisper Medium vs Llama 3.1 8B?
Whisper Medium has 0.77 billion parameters and is specialized for speech recognition, while Llama 3.1 8B has 8 billion parameters and is a general-purpose language model. Llama 3.1 8B is better for text generation but requires more resources.
Can I run Whisper Medium on a Mac?
Yes, you can run Whisper Medium on a Mac. Ensure your Mac has a compatible GPU with at least 1.9 GB of VRAM and the necessary drivers installed.
How much VRAM does Whisper Medium need?
Whisper Medium requires at least 1.9 GB of VRAM to run efficiently. This can vary slightly depending on the quantization level used.
Is Whisper Medium censored?
Whisper Medium is not censored. It is an open-source model released under the MIT license, allowing for unrestricted use and modification.
Is Whisper Medium commercial-use allowed?
Yes, Whisper Medium is licensed under the MIT license, which allows for commercial use without any restrictions.
Whisper Medium context length?
The context length for Whisper Medium is not explicitly defined, but it is designed to handle typical speech segments effectively. For longer audio, you may need to split the input into smaller chunks.
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