Can RTX 4060 Ti 16GB run Stable Diffusion XL (CoreML)?
Yes — runs locally
~78 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4060 Ti 16GB (16 GB VRAM) handles Stable Diffusion XL (CoreML) comfortably using the CoreML quantization, which fits in 3.3 GB. Expected throughput is around 78 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Higher quality image generation. CoreML optimized for iOS. Requires 6GB+ usable memory (iPad/Mac recommended).
Setup tutorial: Stable Diffusion XL (CoreML) on RTX 4060 Ti 16GB
AI-generated, GPU-specific. Verified commands for your exact hardware.
Stable Diffusion XL (CoreML) runs at Grade S on an NVIDIA GeForce RTX 4060 Ti 16GB with ~231 tok/sec using the CoreML quantization (2.8GB file).
Prerequisites
Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, the latest NVIDIA drivers (version 525.60.12 or later), and CUDA 11.8 installed.
Expected performance
With the CoreML quantization, you can expect ~231 tok/sec and 3.3GB VRAM in use, leaving 12.7GB of VRAM headroom for larger context windows. This allows for high-quality image generation with complex prompts.
1. Install runtimeOllama
pip install ollama
ollama init2. Download the model
Download the CoreML quantized version of Stable Diffusion XL (2.8GB file) from Hugging Face.
ollama pull apple/coreml-stable-diffusion-xl-base-ios3. Run it
ollama run apple/coreml-stable-diffusion-xl-base-ios --device cuda
ollama interactive apple/coreml-stable-diffusion-xl-base-ios4. Optimize for RTX 4060 Ti 16GB
For optimal performance on the NVIDIA GeForce RTX 4060 Ti 16GB, set --n-gpu-layers to 32 to utilize the full 16GB VRAM. Enable flash attention (--flash-attn) to speed up inference and reduce memory usage. Given the 16GB VRAM, you can handle larger context windows without running out of memory.
Troubleshooting
Out of memory errors during inference
Reduce the --n-gpu-layers value to 24 or 16 to lower VRAM usage.
Slow inference times
Ensure CUDA is properly installed and the device is set to 'cuda'. Enable flash attention (--flash-attn) for faster inference.
Model fails to load
Check if the model file is corrupted or incomplete. Re-download the model using 'ollama pull apple/coreml-stable-diffusion-xl-base-ios'.
Alternative runtimes
For users preferring a different runtime, consider LM Studio for a more user-friendly GUI, llama.cpp for lightweight and portable deployment, or Jan for advanced customization options. Ollama is recommended for its ease of use and strong performance on this GPU.
Other models that run great on RTX 4060 Ti 16GB
FAQ (20)
What GPU do I need to run Stable Diffusion XL (CoreML)?
Stable Diffusion XL (CoreML) is optimized for iOS devices and does not require a specific GPU. It leverages the Metal Performance Shaders (MPS) framework on iPad and Mac.
Is Stable Diffusion XL (CoreML) good for coding?
Stable Diffusion XL (CoreML) is primarily designed for generating high-quality images and is not optimized for coding tasks.
Stable Diffusion XL (CoreML) vs Llama 3.1 8B?
Stable Diffusion XL (CoreML) is an image generation model with 3.5B parameters, while Llama 3.1 8B is a text generation model with 8B parameters. They serve different purposes and are not directly comparable.
Can I run Stable Diffusion XL (CoreML) on a Mac?
Yes, Stable Diffusion XL (CoreML) can run on a Mac, but it requires at least 6GB of usable memory and is optimized for iOS devices like iPads.
How much VRAM does Stable Diffusion XL (CoreML) need?
Stable Diffusion XL (CoreML) requires 3.3 GB of VRAM, which is consistent across different quantization levels.
Is Stable Diffusion XL (CoreML) censored?
The model is not inherently censored, but it adheres to the CreativeML OpenRail-M license, which may have usage guidelines and restrictions.
Is Stable Diffusion XL (CoreML) commercial-use allowed?
Yes, Stable Diffusion XL (CoreML) can be used commercially, but you must comply with the terms of the CreativeML OpenRail-M license.
Stable Diffusion XL (CoreML) context length?
The context length for Stable Diffusion XL (CoreML) is not specified, as it is primarily an image generation model and does not handle text input in the same way as language models.
Want personalized recommendations for your exact setup? Detect my hardware →