Phi-4
Parameters
14B
Context Length
16K
Modality
Text
Architecture
Dense
License
MIT License
Release Date
13 Dec 2024
Knowledge Cutoff
Nov 2024
API Pricing (per 1M)
Input: $0.13 · Output: $0.50
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
16,000 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#149
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.704 | 40 |
Graduate-Level QA | 0.561 | 99 |
General Text | 1256 | 154 |
Intelligence Index | 0.06 | 276 |
General Knowledge Reference | 0.848 | 14 |
Rankings
Overall Rank
#149
Coding Rank
-
About Phi-4
Phi-4 is Microsoft's 14B parameter dense transformer model engineered with synthetic reasoning data for complex mathematics, logic, and scientific problem-solving. It delivers high-accuracy reasoning across a 16K token context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
24
Key-Value Heads
8
Attention Head Dimension
-
Position Embedding
ROPE
RoPE Theta
250,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
Swish
Dimensions
Auxiliary Parameters
-
Hidden Dimension Size
3,072
Number of Layers
40
FFN Intermediate Size (Dense)
17,920
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
100,352
About Phi-4
The Microsoft Phi-4 model family comprises small language models prioritizing efficient, high-capability reasoning. Its development emphasizes robust data quality and sophisticated synthetic data integration. This approach enables enhanced performance and on-device deployment capabilities.