Can RTX 5060 Ti run Phi-3.5 Mini 3.8B?

Yes — runs locally

~114 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

16 GB

Model size

3.8B

Best quant

Q8_0

VRAM needed

4.3 GB

The verdict

The RTX 5060 Ti (16 GB VRAM) handles Phi-3.5 Mini 3.8B comfortably using the Q8_0 quantization, which fits in 4.3 GB. Expected throughput is around 114 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Tiny but capable 3.8B model. Runs on almost any hardware including phones.

Setup tutorial: Phi-3.5 Mini 3.8B on RTX 5060 Ti

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

TL;DR

Run Phi-3.5 Mini 3.8B on an NVIDIA GeForce RTX 5060 Ti with Grade S performance at ~178 tok/sec using the Q8_0 quantization. Requires 4.3GB VRAM.

Prerequisites

Before starting, ensure you have at least 4GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 525.60.13 or later), and CUDA 11.8 or later installed.

Expected performance

You can expect the model to run at approximately 178 tokens per second with 4.3GB VRAM in use, leaving 11.7GB of VRAM available for context. This allows for a practical context window of around 131,072 tokens, making it highly efficient for long-form text generation.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q8_0 quantized version of Phi-3.5 Mini 3.8B, which is a 3.8GB file.

ollama pull bartowski/Phi-3.5-mini-instruct-GGUF:Phi-3.5-mini-instruct-Q8_0.gguf

3. Run it

ollama run Phi-3.5-mini-instruct-Q8_0 --n-gpu-layers 32 --flash-attn
ollama chat Phi-3.5-mini-instruct-Q8_0

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 efficiently. Enable --flash-attn to speed up attention computations. With 4.3GB VRAM used by the model, you have 11.7GB of VRAM left for context, allowing for a large practical context window.

Troubleshooting

Low token generation speed

Ensure that --flash-attn is enabled and that --n-gpu-layers is set to 32. If the issue persists, check your CUDA installation and driver versions.

Out of memory errors

Reduce the number of --n-gpu-layers to 24 or 16 to lower VRAM usage. Alternatively, try running the model with a smaller context window.

Model not loading

Verify that the model file was downloaded correctly and that the Ollama runtime is properly installed. Re-run the 'ollama pull' command to ensure the model is up-to-date.

Alternative runtimes

Alternative runtimes like LM Studio, llama.cpp, and Jan can be used if you need more customization or specific features. LM Studio is ideal for GUI-based interaction, llama.cpp offers more control over quantization and performance tuning, and Jan is suitable for lightweight, low-resource environments. However, Ollama provides a balanced approach with ease of use and good performance on the NVIDIA GeForce RTX 5060 Ti.

Full Phi-3.5 Mini 3.8B details →

Other models that run great on RTX 5060 Ti

FAQ (20)

What GPU do I need to run Phi-3.5 Mini 3.8B?

Phi-3.5 Mini 3.8B requires a GPU with at least 2.7 GB of VRAM, but 4.3 GB is recommended for optimal performance.

Is Phi-3.5 Mini 3.8B good for coding?

Phi-3.5 Mini 3.8B is capable of generating code and providing coding assistance, but its performance is best suited for simpler tasks due to its 3.8B parameters.

Phi-3.5 Mini 3.8B vs Llama 3.1 8B?

Phi-3.5 Mini 3.8B has 3.8B parameters, making it smaller and more resource-efficient than Llama 3.1 8B, which has 8B parameters and requires more VRAM and computational power.

Can I run Phi-3.5 Mini 3.8B on a Mac?

Yes, Phi-3.5 Mini 3.8B can run on a Mac, provided your Mac has a compatible GPU with at least 2.7 GB of VRAM.

How much VRAM does Phi-3.5 Mini 3.8B need?

Phi-3.5 Mini 3.8B requires a minimum of 2.7 GB of VRAM, but 4.3 GB is recommended for better performance, depending on the quantization level.

Is Phi-3.5 Mini 3.8B censored?

Phi-3.5 Mini 3.8B is not inherently censored, but it may include content filters to prevent harmful or inappropriate content.

Is Phi-3.5 Mini 3.8B commercial-use allowed?

Yes, Phi-3.5 Mini 3.8B is licensed under the MIT License, which allows for commercial use.

Phi-3.5 Mini 3.8B context length?

Phi-3.5 Mini 3.8B supports a context length of 131,072 tokens, which is quite large and allows for extensive context in conversations and tasks.

Want personalized recommendations for your exact setup? Detect my hardware →