Can RTX 4060 Ti 16GB run Phi-3.5 Vision?

Yes — runs locally

~78 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

16 GB

Model size

4.2B

Best quant

Q4_K_M

VRAM needed

3.2 GB

The verdict

The RTX 4060 Ti 16GB (16 GB VRAM) handles Phi-3.5 Vision comfortably using the Q4_K_M quantization, which fits in 3.2 GB. Expected throughput is around 78 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Vision-language model from Microsoft. Can understand images and documents.

Setup tutorial: Phi-3.5 Vision on RTX 4060 Ti 16GB

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

TL;DR

Run Phi-3.5 Vision on an NVIDIA GeForce RTX 4060 Ti 16GB with Grade S performance, using the Q4_K_M quantization for ~233 tok/sec.

Prerequisites

Before starting, ensure you have at least 5GB 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 recommended settings, you can expect ~233 tok/sec performance, with 3.2GB VRAM in use. The remaining 12.8GB VRAM provides ample headroom for handling large context windows, enabling efficient processing of complex multimodal tasks.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q4_K_M quantized Phi-3.5 Vision model (2.5GB) from Hugging Face.

ollama pull abetlen/Phi-3.5-vision-instruct-gguf:Phi-3.5-vision-instruct-Q4_K_M.gguf

3. Run it

ollama run --model abetlen/Phi-3.5-vision-instruct-gguf --quant Q4_K_M --n-gpu-layers 128 --flash-attn
ollama chat --model abetlen/Phi-3.5-vision-instruct-gguf --quant Q4_K_M

4. Optimize for RTX 4060 Ti 16GB

For optimal performance on the NVIDIA GeForce RTX 4060 Ti 16GB, set --n-gpu-layers to 128 to utilize the 16GB VRAM effectively. Enable --flash-attn for faster inference and better memory efficiency. Given the 16GB VRAM, you can allocate up to 3.2GB for the model, leaving 12.8GB for context, which allows for a large practical context window.

Troubleshooting

Out of memory errors during inference

Reduce --n-gpu-layers to 64 or enable --cpu-offload to offload some layers to CPU.

Slow inference speed

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

Model not loading

Verify that the model file is correctly downloaded and not corrupted. Try re-downloading the model using the 'ollama pull' command.

Alternative runtimes

For users preferring different runtimes, consider LM Studio for a more user-friendly GUI, llama.cpp for advanced customization options, or Jan for lightweight deployment. Each runtime has its strengths, but Ollama provides a balanced approach for ease of use and performance on the NVIDIA GeForce RTX 4060 Ti 16GB.

Full Phi-3.5 Vision details →

Other models that run great on RTX 4060 Ti 16GB

FAQ (20)

What GPU do I need to run Phi-3.5 Vision?

To run Phi-3.5 Vision, you need a GPU with at least 3.2 GB of VRAM. Higher VRAM will improve performance, especially for larger tasks.

Is Phi-3.5 Vision good for coding?

Phi-3.5 Vision is primarily designed for vision and language tasks, such as understanding images and documents. It may not be as optimized for coding-specific tasks compared to models like Codex or CodeLlama.

Phi-3.5 Vision vs Llama 3.1 8B?

Phi-3.5 Vision has 4.2 billion parameters and is specialized for vision-language tasks, while Llama 3.1 8B is a text-only model with 8 billion parameters, making it more versatile for text generation but less suited for image understanding.

Can I run Phi-3.5 Vision on a Mac?

Yes, you can run Phi-3.5 Vision on a Mac, but ensure your Mac has a compatible GPU with at least 3.2 GB of VRAM. Apple Silicon GPUs may require additional drivers or software.

How much VRAM does Phi-3.5 Vision need?

Phi-3.5 Vision requires 3.2 GB of VRAM, which is consistent across different quantization levels. More VRAM can help with larger batch sizes and more complex tasks.

Is Phi-3.5 Vision censored?

Phi-3.5 Vision is not inherently censored, but it adheres to ethical guidelines and may have filters to prevent harmful content. Users can configure additional safety measures as needed.

Is Phi-3.5 Vision commercial-use allowed?

Yes, Phi-3.5 Vision is licensed under the MIT License, which allows for commercial use. However, always review the specific terms of the license to ensure compliance.

Phi-3.5 Vision context length?

Phi-3.5 Vision has a context length of 131,072 tokens, allowing it to process very long sequences of text and images effectively.

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