Activefastllm Open Source

Phi-4 Mini

by Microsoft· Released February 2025· Cutoff October 2024

Phi-4 Mini is a compact, efficient language model from Microsoft, designed for high-performance reasoning and coding tasks with a 128K token context window. It is part of the Phi-4 family, offering strong capabilities in a smaller footprint suitable for edge and resource-constrained environments. The model emphasizes speed and accuracy for text generation and code understanding.

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

text

Parameters

3.8B

License

MIT

Capabilities

Text GenerationCode GenerationReasoningFunction CallingStreamingJSON Mode

Best For

Efficient reasoning and code generation tasks in resource-constrained or latency-sensitive applications.

Strengths

Compact size with strong reasoning performance
128K token context window
Open-source availability
Optimized for fast inference
Good coding benchmark scores

Limitations

Smaller parameter count may limit complex reasoning compared to larger models
No native multimodal support (text-only)
Less extensive training data than frontier models
May not match top-tier models on highly specialized tasks

Use Cases

Code generation and completion

Chatbots and virtual assistants

Text summarization

Question answering

Data extraction and parsing

Educational tools

Edge device deployment

Improvements Over Previous Model

New model in the Phi-4 family, succeeding Phi-3.5-mini
Context window increased from 128K to 128K (same as Phi-3.5-mini)
Improved reasoning and coding benchmarks over Phi-3.5-mini
Smaller parameter count (3.8B vs 3.8B) but better performance
Open-source under MIT license (same as Phi-3.5-mini)
Optimized for faster inference on edge devices

Back to all models

Activefastllm Open Source

Phi-4 Mini

by Microsoft· Released February 2025· Cutoff October 2024

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

text

Parameters

3.8B

License

MIT

Capabilities

Text GenerationCode GenerationReasoningFunction CallingStreamingJSON Mode

Best For

Efficient reasoning and code generation tasks in resource-constrained or latency-sensitive applications.

Strengths

Compact size with strong reasoning performance
128K token context window
Open-source availability
Optimized for fast inference
Good coding benchmark scores

Limitations

Smaller parameter count may limit complex reasoning compared to larger models
No native multimodal support (text-only)
Less extensive training data than frontier models
May not match top-tier models on highly specialized tasks

Use Cases

Code generation and completion

Chatbots and virtual assistants

Text summarization

Question answering

Data extraction and parsing

Educational tools

Edge device deployment

Improvements Over Previous Model

New model in the Phi-4 family, succeeding Phi-3.5-mini
Context window increased from 128K to 128K (same as Phi-3.5-mini)
Improved reasoning and coding benchmarks over Phi-3.5-mini
Smaller parameter count (3.8B vs 3.8B) but better performance
Open-source under MIT license (same as Phi-3.5-mini)
Optimized for faster inference on edge devices

Back to all models