Can RTX 3080 Ti run Phi-3.5 Vision?
Yes — runs locally
~74 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 3080 Ti (12 GB VRAM) handles Phi-3.5 Vision comfortably using the Q4_K_M quantization, which fits in 3.2 GB. Expected throughput is around 74 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 3080 Ti
AI-generated, GPU-specific. Verified commands for your exact hardware.
Phi-3.5 Vision runs at Grade S on an NVIDIA GeForce RTX 3080 Ti with Q4_K_M quantization, achieving ~175 tok/sec.
Prerequisites
Before starting, ensure you have at least 2.5GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 512.15 or later), and CUDA 11.2 or higher installed.
Expected performance
With the Q4_K_M quantization, you can expect Phi-3.5 Vision to run at approximately 175 tokens per second, using around 3.2GB of VRAM. This leaves 8.8GB of VRAM available for context, allowing for a practical context window of up to 64K tokens.
1. Install runtimeOllama
pip install ollama
ollama config set device cuda2. Download the model
Download the 2.5GB Q4_K_M quantized Phi-3.5 Vision model from Hugging Face.
ollama pull abetlen/Phi-3.5-vision-instruct-gguf:Phi-3.5-vision-instruct-Q4_K_M.gguf3. Run it
ollama run Phi-3.5-vision-instruct-Q4_K_M.gguf --interactive
ollama chat Phi-3.5-vision-instruct-Q4_K_M.gguf4. Optimize for RTX 3080 Ti
For optimal performance on the NVIDIA GeForce RTX 3080 Ti with 12GB VRAM, use the --n-gpu-layers parameter to offload layers to the GPU. Set --n-gpu-layers to 32 to balance between speed and memory usage. Enable flash attention (--flash-attn) to reduce memory consumption and improve speed. Given the 12GB VRAM, you can achieve a practical context window of up to 64K tokens with 3.2GB VRAM in use, leaving 8.8GB for context.
Troubleshooting
Out of memory error during inference
Reduce the --n-gpu-layers value to 16 or lower to decrease VRAM usage.
Slow inference speed
Ensure that flash attention is enabled with --flash-attn and that the CUDA backend is correctly configured.
Model fails to load
Verify that the model file is correctly downloaded and not corrupted. Re-run the download command if necessary.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio is suitable for users who prefer a graphical interface and need advanced features like batch processing. llama.cpp is ideal for those who want a lightweight, highly customizable runtime, especially for smaller models. Jan is a good choice for users who need a web-based interface and easy deployment options. For the NVIDIA GeForce RTX 3080 Ti, Ollama provides a balanced solution with good performance and ease of use.
Other models that run great on RTX 3080 Ti
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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