Microsoft
Phi-4 Mini 3.8B
Latest Phi mini with strong reasoning. Drop-in upgrade from Phi-3.5 Mini.
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
| Quantization | Bits | File Size | VRAM Needed | RAM Needed | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.5 | 2.321 GB | 2.82 GB | 3.32 GB | 85% |
| Q8_0 | 8 | 3.804 GB | 4.3 GB | 4.8 GB | 98% |
See It In Action
Real model outputs generated via RunThisModel.com — watch responses stream in real time.
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.