Model ID
microsoft/Phi-4-reasoning-plus
Capabilities
Phi 4 Reasoning Plus
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.
About this model
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.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (microsoft/Phi-4-reasoning-plus). Released under MIT. Further reading: Paper · Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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