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Phi-4 Reasoning Plus

Parameters

14B

Context Length

32.768K

Modality

Text

Architecture

Dense

License

MIT

Release Date

-

Knowledge Cutoff

Mar 2025

Technical Specifications

Attention Structure

Multi-Head Attention

Hidden Dimension Size

-

Number of Layers

-

Attention Heads

-

Key-Value Heads

-

Activation Function

-

Normalization

-

Position Embedding

Absolute Position Embedding

System Requirements

VRAM requirements for different quantization methods and context sizes

Phi-4 Reasoning Plus

Microsoft's Phi-4 Reasoning Plus is a 14-billion parameter language model specifically optimized for complex reasoning tasks. It is an enhanced variant within the Phi-4 family, building upon the base Phi-4 model. The model's primary purpose is to address scenarios requiring long-chain reasoning, such as advanced mathematics, scientific inquiry, and code generation. Its development emphasizes delivering high-quality outputs even in computationally constrained environments.

The architecture of Phi-4 Reasoning Plus is a dense, decoder-only Transformer. It incorporates an extended context window of 32,000 tokens to facilitate processing of lengthy reasoning chains. The model utilizes rotary position embeddings to maintain coherence and track token positions effectively across extended sequences. Training involved supervised fine-tuning on a curated dataset of chain-of-thought traces, along with reinforcement learning to further enhance performance. This methodology focuses on high-quality synthetic and filtered organic data, ensuring proficiency in complex problem-solving.

Phi-4 Reasoning Plus demonstrates an increased latency compared to its counterpart, Phi-4 Reasoning, due to its generation of approximately 50% more tokens for more detailed responses. This characteristic makes it particularly suitable for high-accuracy tasks where comprehensive reasoning is paramount. The model is designed to operate efficiently on consumer-grade hardware, including mobile devices, tablets, and desktops, thereby expanding its accessibility for various AI applications.

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.


Other Phi-4 Models

Evaluation Benchmarks

Ranking is for Local LLMs.

Rank

#17

BenchmarkScoreRank

Graduate-Level QA

GPQA

0.69

5

Professional Knowledge

MMLU Pro

0.76

6

0.61

9

General Knowledge

MMLU

0.69

10

0.58

12

0.63

13

Agentic Coding

LiveBench Agentic

0.05

14

0.55

15

Rankings

Overall Rank

#17

Coding Rank

#19

GPU Requirements

Full Calculator

Choose the quantization method for model weights

Context Size: 1,024 tokens

1k
16k
32k

VRAM Required:

Recommended GPUs

Phi-4 Reasoning Plus: Specifications and GPU VRAM Requirements