Phi-4 Mini

What this model is

The architecture is dense. Every parameter is part of the active path, so memory and speed scale with the full model rather than a smaller expert subset.

Memory and quantization

Decimal GB, rounded from the Ollama tag page. Runtime memory still needs KV cache and overhead.

Estimate formula: published weight files + 1.0737 GB per 8K tokens × context / 8K + 1.5 GB runtime overhead. Sizes are decimal GB, not GiB. At 8K context, the smallest listed build is about 5.1 GB before OS and application reserve.

Conservative FP16 estimate from the Phi-4 Mini GQA configuration; not a runtime measurement.

KV method source: https://ollama.com/library/phi4-mini

Speed heuristic

Speed depends on quantization, backend, and hardware; no single measured value is reported

Active path: 3.8B parameters. This is a relative speed signal only; it is not a tokens/sec benchmark.

Runtimes

• Ollama
• llama.cpp

ollama run phi4-mini

License restrictions

MIT permits commercial use and modification; preserve the copyright and permission notice.

This is a plain-language summary, not legal advice. Read the linked license before commercial deployment or redistribution.

Known issues

• Not intended for long-context or highly complex tasks

Sources

• https://ollama.com/library/phi4-mini
• https://huggingface.co/microsoft/Phi-4-mini-instruct

This page is an independent compatibility guide, not official documentation. Verify the primary source before downloading or deploying a model.