Activefastmultimodal Open Source

Phi-4 Multimodal

by Microsoft· Released February 2025

Phi-4 Multimodal is a compact, efficient multimodal model from Microsoft that processes text, images, and audio inputs. It is designed for on-device and edge scenarios, offering strong performance in vision and speech tasks while maintaining a small footprint. Part of the Phi-4 family, it balances capability with low computational cost.

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

textimageaudio

License

MIT

Capabilities

Vision (image understanding)Audio (speech recognition and understanding)Multimodal reasoningCode generationFunction CallingStreaming

Best For

On-device and edge applications requiring multimodal understanding with low latency and small model size.

Strengths

Compact size enables deployment on resource-constrained devices
Strong multimodal performance relative to model size
Supports text, image, and audio inputs natively
Efficient inference with low latency

Limitations

Smaller parameter count may limit complex reasoning compared to larger models
Not as capable as frontier models in highly specialized tasks
Limited to 128K context window
May not support all languages equally

Use Cases

On-device virtual assistants with vision and speech

Real-time document analysis and transcription

Edge-based image captioning and audio transcription

Smart home devices with multimodal interaction

Accessibility tools for visually or hearing impaired users

Automated customer service with image and voice input

Educational tools for interactive learning

Improvements Over Previous Model

Adds native multimodal support (vision and audio) compared to text-only Phi-4
Smaller and more efficient than Phi-3.5 vision models
Improved performance on vision-language benchmarks over Phi-3.5
Supports audio input, a new capability not present in previous Phi models

Back to all models

Activefastmultimodal Open Source

Phi-4 Multimodal

by Microsoft· Released February 2025

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

textimageaudio

License

MIT

Capabilities

Vision (image understanding)Audio (speech recognition and understanding)Multimodal reasoningCode generationFunction CallingStreaming

Best For

On-device and edge applications requiring multimodal understanding with low latency and small model size.

Strengths

Compact size enables deployment on resource-constrained devices
Strong multimodal performance relative to model size
Supports text, image, and audio inputs natively
Efficient inference with low latency

Limitations

Smaller parameter count may limit complex reasoning compared to larger models
Not as capable as frontier models in highly specialized tasks
Limited to 128K context window
May not support all languages equally

Use Cases

On-device virtual assistants with vision and speech

Real-time document analysis and transcription

Edge-based image captioning and audio transcription

Smart home devices with multimodal interaction

Accessibility tools for visually or hearing impaired users

Automated customer service with image and voice input

Educational tools for interactive learning

Improvements Over Previous Model

Adds native multimodal support (vision and audio) compared to text-only Phi-4
Smaller and more efficient than Phi-3.5 vision models
Improved performance on vision-language benchmarks over Phi-3.5
Supports audio input, a new capability not present in previous Phi models

Back to all models