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Microsoft Phi

Microsoft Phi-4 and Phi-3 - compact open-source LLMs for edge and local deployments. GDPR-compliant via self-hosting. AI consulting from Germany.

License MIT
GDPR Hosting Available
Context 16k (Phi-4), up to 128k (Phi-3 variants) Tokens
Modality Text, Image → Text

Versions

Overview of available model variants

ModelReleaseEUStrengthsWeaknessesStatus
Phi-4 Recommended
2024-12
14B parameters - very efficient Strong reasoning capabilities
Smaller than frontier models
Current
Phi-3.5-MoE
2024
Mixture-of-Experts 42B parameters (16 active)
Current
Phi-3.5-mini
2024
3.8B parameters Runs on smartphones
Limited capacity
Current
Phi-3.5-vision
2024
Multimodal Image understanding
Current
Phi-3-medium
2024
14B parameters Balance of size and performance
Current

Use Cases

Typical applications for this model

Edge AI & IoT
Mobile Applications
Offline Scenarios
Embedded Systems
Resource-Constrained Environments
Coding Assistants
Local LLM Deployments

Technical Details

API, features and capabilities

API & Availability
Availability Public
Latency (TTFT) ~100ms (local)
Throughput Hardware-dependent Tokens/Sec
Features & Capabilities
Tool Use Function Calling Structured Output Vision Reasoning Mode File Upload
Training & Knowledge
Knowledge Cutoff 2024-10
Fine-Tuning Available (LoRA, QLoRA, Full Fine-Tuning)
Language Support
Best Quality English, German
Supported 20+ languages
Optimized for English, usable quality in German

Hosting & Compliance

GDPR-compliant hosting options and licensing

GDPR-Compliant Hosting Options
Self-Hosted
Own Infrastructure
Recommended - full data control
Azure
West Europe / Germany
Azure AI Model Catalog
Ollama
Local
Easy local deployment
License & Hosting
License MIT
Security Filters Customizable
Enterprise Support Yes
SLA Available Yes
On-Premise Edge-capable

As AI consultants based in Rosenheim, Germany, we recommend Microsoft Phi for enterprises that want to run powerful AI on resource-constrained hardware. Phi models offer impressive performance with minimal requirements.

Small Language Models (SLMs)

Microsoft Phi is Microsoft’s family of “Small Language Models” - compact but powerful models specifically optimized for efficiency.

Why Phi for Enterprises?

  • Compact: 3.8B to 14B parameters
  • Efficient: Runs on consumer hardware
  • MIT License: Full commercial use permitted
  • Self-Hosting: Full data control
  • Edge-Ready: Smartphones, IoT, embedded

Key Strengths

Efficiency

Phi models achieve impressive performance at minimal size:

ModelParametersComparable Performance to
Phi-414BGPT-4 (partially)
Phi-3.5-MoE42B (16 active)Llama 3 70B
Phi-3.5-mini3.8BLlama 3 8B

Local Deployment

Phi models can be operated completely locally:

  • Ollama: ollama run phi4
  • LM Studio: Simple GUI
  • vLLM: Production deployment
  • ONNX: Optimized inference

Hardware Requirements

ModelRAM/VRAMRecommended Hardware
Phi-416 GBRTX 4070 / M2 Mac
Phi-3.5-MoE24 GBRTX 4090
Phi-3.5-mini4 GBLaptop / Smartphone
Phi-3.5-vision8 GBRTX 3060

Reasoning Strength

Phi-4 shows particularly strong reasoning capabilities:

  • Mathematics and logic
  • Coding tasks
  • Structured analysis
  • Chain-of-thought

Comparison to Other SLMs

FeaturePhi-4Llama 3.2 3BGemma 2 2B
Parameters14B3B2B
ReasoningStrongMediumMedium
CodingStrongGoodGood
VisionYes (3.5)NoNo
LicenseMITCommunityApache 2.0

Integration with CompanyGPT

Microsoft Phi can be integrated in CompanyGPT as a self-hosted option - ideal for enterprises that want to operate AI without cloud dependency.

Our Recommendation

Microsoft Phi-4 is our top recommendation for local and edge deployments. For smartphones and IoT, Phi-3.5-mini is ideal, for multimodal applications Phi-3.5-vision.

For applications requiring maximum quality where cloud hosting is acceptable, we recommend OpenAI GPT or Anthropic Claude instead.

Consultation for this model?

We help you select and integrate the right AI model for your use case.