Model ID
microsoft/phi-4
Capabilities
Phi 4
Phi 4 is a dense transformer model designed for high-quality reasoning and efficient deployment in constrained environments. It features 14B parameters with 40 layers, 5,120 hidden size, and 40 attention heads with 10 key-value heads. The model supports a 16K token context window and is trained on 9.8T tokens using a mix of synthetic and curated data. It is optimized with supervised fine-tuning and direct preference optimization for strong instruction-following and low-latency inference.
About this model
Phi 4 is a dense transformer model designed for high-quality reasoning and efficient deployment in constrained environments. It features 14B parameters with 40 layers, 5,120 hidden size, and 40 attention heads with 10 key-value heads. The model supports a 16K token context window and is trained on 9.8T tokens using a mix of synthetic and curated data. It is optimized with supervised fine-tuning and direct preference optimization for strong instruction-following and low-latency inference.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (microsoft/phi-4). 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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