Phi-3-medium
Parameters
14B
Context Length
128K
Modality
Text
Architecture
Dense
License
MIT
Release Date
22 Apr 2024
Knowledge Cutoff
Oct 2023
API Pricing (per 1M)
Input: $0.17 · Output: $0.68
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
128,000 tokens
Consumer
3x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#205
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1198 | 159 |
Rankings
Overall Rank
#205
Coding Rank
-
About Phi-3-medium
Phi-3-medium is Microsoft's 14B parameter dense foundation model delivering advanced reasoning and code synthesis in compute-constrained environments. Optimized for ONNX Runtime, it supports extended context lengths up to 128K tokens.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
40
Key-Value Heads
10
Attention Head Dimension
-
Position Embedding
ROPE
RoPE Theta
10,000
Sliding Window Attention
Yes
Sliding Window Size
2,047
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
Swish
Dimensions
Hidden Dimension Size
5,120
Number of Layers
40
FFN Intermediate Size (Dense)
17,920
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
32,064
About Phi-3
Microsoft's Phi-3 models are small language models designed for efficient operation on resource-constrained devices. They utilize a transformer decoder architecture and are trained on extensively filtered, high-quality data, including synthetic compositions. This approach enables a compact yet capable model family.