S
S
Home / Models / Phi-3 Small

Phi-3 Small

by Microsoft

7.9
KYI Score

Balanced Phi-3 model with good performance and efficiency.

LLMMITFREE7B
Official WebsiteHugging Face

Quick Facts

Model Size
7B
Context Length
128K tokens
Release Date
May 2024
License
MIT
Provider
Microsoft
KYI Score
7.9/10

Best For

→Chatbots
→Content generation
→Edge deployment
→General tasks

Performance Metrics

Speed

9/10

Quality

7/10

Cost Efficiency

10/10

Specifications

Parameters
7B
Context Length
128K tokens
License
MIT
Pricing
free
Release Date
May 21, 2024
Category
llm

Key Features

EfficientLong contextFastMIT license

Pros & Cons

Pros

  • ✓Good balance
  • ✓Long context
  • ✓MIT license
  • ✓Efficient

Cons

  • !Smaller model
  • !Limited capabilities

Ideal Use Cases

Chatbots

Content generation

Edge deployment

General tasks

Phi-3 Small FAQ

What is Phi-3 Small best used for?

Phi-3 Small excels at Chatbots, Content generation, Edge deployment. Good balance, making it ideal for production applications requiring llm capabilities.

How does Phi-3 Small compare to other models?

Phi-3 Small has a KYI score of 7.9/10, with 7B parameters. It offers good balance and long context. Check our comparison pages for detailed benchmarks.

What are the system requirements for Phi-3 Small?

Phi-3 Small with 7B requires appropriate GPU memory. Smaller quantized versions can run on consumer hardware, while full precision models need enterprise GPUs. Context length is 128K tokens.

Is Phi-3 Small free to use?

Yes, Phi-3 Small is free and licensed under MIT. You can deploy it on your own infrastructure without usage fees or API costs, giving you full control over your AI deployment.

Related Models

LLaMA 3.1 405B

9.4/10

Meta's largest and most capable open-source language model with 405 billion parameters, offering state-of-the-art performance across reasoning, coding, and multilingual tasks.

llm405B

LLaMA 3.1 70B

9.1/10

A powerful 70B parameter model that balances performance and efficiency, ideal for production deployments requiring high-quality outputs.

llm70B

BGE M3

9.1/10

Multi-lingual, multi-functionality, multi-granularity embedding model.

llm568M