base_model: microsoft/Phi-4-reasoning-plus
This is a quantization of the Phi-4-reasoning-plus.
Phi-4-reasoning-plus, developed by Microsoft Research, stands out as a state-of-the-art language model specialized in reasoning and logic, particularly excelling in domains like math, science, and coding. Finetuned from the Phi-4 model, it uniquely combines supervised learning with reinforcement learning, enhancing accuracy and offering advanced reasoning capabilities in memory-constrained and latency-sensitive environments. The model generates responses with a distinct two-section format: a detailed reasoning chain-of-thought process followed by a concise solution, ensuring thorough and accurate answers. Despite being relatively compact with 14 billion parameters, it delivers strong performance across a wide range of complex reasoning tasks and demonstrates the capacity to maintain coherence over extended inputs, making it particularly suited for deep, multi-step reasoning applications.
Evaluations
This model provides an accuracy recovery of 100.0%.
| English | Phi-4-reasoning-plus | Phi-4-reasoning-plus-FP8-Dynamic (this) |
|---|---|---|
| Avg. | 70.77 | 70.77 |
| ARC | 65.7 | 65.5 |
| Hellaswag | 69 | 69.5 |
| MMLU | 77.61 | 77.3 |
We did not check for data contamination.
Evaluation was done using Eval. Harness with limit=1000.
Usage
Install vLLM and run the server:
python -m vllm.entrypoints.openai.api_server --model cortecs/Phi-4-reasoning-plus-FP8-Dynamic --max-model-len 32768 --gpu-memory-utilization 0.95
Access the model:
curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' {
"model": "cortecs/Phi-4-reasoning-plus-FP8-Dynamic",
"prompt": "San Francisco is a"
} '