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Phi 4 Reasoning Plus

NVIDIA
Phi 4 Reasoning Plus is a dense transformer model optimized for advanced chain-of-thought reasoning across math, science, and coding tasks. It builds on Phi-4 with enhanced performance through supervised fine-tuning and outcome-based reinforcement learning for longer reasoning traces. The model features 14B parameters with 40 layers, 5,120 hidden size, and 40 attention heads with 10 key-value heads. It supports a 32K token context window and is trained on high-quality curated and synthetic data, delivering improved reasoning accuracy at the cost of higher latency.
TypeDense LLM
CapabilitiesText Generation, Instruction Following, Reasoning, Mathematical Reasoning+2 more
Release Date30 April, 2025
Links
Paper|Blog|HF Model Card
LicenseMIT

Inference Instructions

Deploy and run this model on NVIDIA B200 GPUs using the command below. Copy the command to get started with inference.

CONSOLE
docker run -it --rm 
 --runtime=nvidia 
 --gpus all 
 --ipc=host 
 --shm-size=128g 
 -p 8000:8000 
 -v ~/.cache/huggingface:/root/.cache/huggingface 
 -e HF_TOKEN='YOUR_HF_TOKEN' 
 vllm/vllm-openai:v0.18.1 
 microsoft/Phi-4-reasoning-plus 
  --tensor-parallel-size 2 
 --max-model-len auto 
 --gpu-memory-utilization 0.95 
 --max-num-batched-tokens 65536 
 --max-num-seqs 1024 
 --trust-remote-code

Model Benchmarks

Each model was tested with a fixed input size and total token volume while increasing concurrency to measure serving performance under load.

ITL vs Concurrency

Time to First Token

Throughput Scaling

Total Tokens/sec vs Avg TTFT

Vultr Cloud GPU

NVIDIA HGX B200

Deploy NVIDIA B200 on Vultr Cloud GPU

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