Microsoft

Phi-4 Mini 3.8B

Latest Phi mini with strong reasoning. Drop-in upgrade from Phi-3.5 Mini.

3.8B parametersphi4mit128K context2.82GB - 4.3GB VRAM

About This Model

Phi-4 Mini 3.8B is a compact yet powerful language model developed by Microsoft, designed for efficient local deployment. With 3.8 billion parameters, this model excels in generating coherent and contextually rich text across a wide range of applications, including content creation, chatbot interactions, and summarization tasks. The model’s architecture, known as phi4, allows it to handle large context lengths up to 131,072 tokens, making it particularly useful for tasks that require deep contextual understanding, such as long-form writing or detailed document analysis. Despite its relatively modest size, Phi-4 Mini 3.8B punches well above its weight, offering performance and output quality that rival larger models while consuming significantly less computational resources.

In terms of efficiency, Phi-4 Mini 3.8B stands out in its size class. It requires only 2.8 to 4.3 GB of VRAM, making it accessible for users with mid-range GPUs. This efficiency, combined with the availability of quantizations like Q4_K_M and Q8_0, ensures that the model can be deployed on a variety of hardware setups, from high-end workstations to more modest consumer-grade systems. Ideal users include developers, content creators, and businesses looking to leverage advanced text generation capabilities without the need for expensive cloud services. For those with limited hardware resources, Phi-4 Mini 3.8B offers a compelling balance of performance and resource efficiency, making it a versatile choice for a broad spectrum of applications.

Check Your Hardware

See which quantizations of Phi-4 Mini 3.8B your hardware can run.

Quantization Options

QuantizationBitsFile SizeVRAM NeededRAM NeededQuality
Q4_K_M4.52.321 GB2.82 GB3.32 GB
85%
Q8_083.804 GB4.3 GB4.8 GB
98%

See It In Action

Real model outputs generated via RunThisModel.com — watch responses stream in real time.

Llama 3.3 70B responding...

Outputs generated by real AI models via RunThisModel.com. Generation speed shown is from cloud inference. Local speeds vary by hardware — check your device.

Frequently Asked Questions

How much VRAM do I need to run Phi-4 Mini 3.8B?

Phi-4 Mini 3.8B requires 2.82GB VRAM minimum with Q4_K_M quantization. For full precision, you need 4.3GB VRAM.

What is the best quantization for Phi-4 Mini 3.8B?

Q4_K_M offers the best balance of quality and VRAM usage. Q8_0 is near-lossless if you have enough VRAM.