Can RTX 5070 Ti run Phi-3.5 Vision?

Yes — runs locally

~114 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 5070 Ti (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 114 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 5070 Ti

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

TL;DR

Phi-3.5 Vision runs at Grade S on the NVIDIA GeForce RTX 5070 Ti with Q4_K_M quantization, achieving ~233 tok/sec.

Prerequisites

Before starting, ensure you have at least 2.5GB of free 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 Phi-3.5 Vision to run at approximately 233 tokens per second, using 3.2GB of VRAM. Given the remaining 12.8GB of VRAM, you can achieve a practical context window of up to 131,072 tokens, allowing for extensive image and document understanding.

1. Install runtimeOllama

pip install ollama
ollama config set cuda

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 Phi-3.5-vision-instruct-Q4_K_M.gguf --n-gpu-layers 32 --flash-attn
ollama chat Phi-3.5-vision-instruct-Q4_K_M.gguf

4. Optimize for RTX 5070 Ti

For optimal performance on the NVIDIA GeForce RTX 5070 Ti with 16GB VRAM, set --n-gpu-layers to 32 to utilize the GPU efficiently. Enable flash attention (--flash-attn) to speed up computations. With 3.2GB VRAM used by the model, you have 12.8GB of VRAM headroom for larger context windows and additional tasks.

Troubleshooting

Model fails to load due to insufficient VRAM

Reduce the number of GPU layers with --n-gpu-layers 16 or lower.

Performance is slower than expected

Ensure that flash attention is enabled with --flash-attn.

CUDA initialization fails

Update your NVIDIA drivers to the latest version and reinstall CUDA 11.8.

Alternative runtimes

Alternative runtimes include LM Studio and llama.cpp. Use LM Studio for a more user-friendly interface and better integration with other models. Use llama.cpp for more advanced customization options and lower-level control over the model execution. For lightweight setups, consider using Jan, which is optimized for smaller models and less powerful GPUs.

Full Phi-3.5 Vision details →

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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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