---
title: deepSeek-r1-distill-qwen-1.5B-intel-npu
canonical_url: "https://www.modelscope.ai/models/NexaAI/deepSeek-r1-distill-qwen-1.5B-intel-npu"
md_url: "https://www.modelscope.ai/models/NexaAI/deepSeek-r1-distill-qwen-1.5B-intel-npu.md"
repository: NexaAI/deepSeek-r1-distill-qwen-1.5B-intel-npu
last_updated: 2025-11-23
model_type:
  - qwen2
architectures:
  - Qwen2ForCausalLM
library_name:
  - pytorch
frameworks:
  - pytorch
downloads: 125
stars: 0
---

# deepSeek-r1-distill-qwen-1.5B-intel-npu

> deepSeek-r1-distill-qwen-1.5B-intel-npu - An open-source model by NexaAI on ModelScope. DeepSeek-r1-distill-qwen-1.5B

- **Repository**: NexaAI/deepSeek-r1-distill-qwen-1.5B-intel-npu
- **Downloads**: 125
- **Stars**: 0
- **Last updated**: 2025-11-23

Source: https://www.modelscope.ai/models/NexaAI/deepSeek-r1-distill-qwen-1.5B-intel-npu

---

# DeepSeek-r1-distill-qwen-1.5B

Run **DeepSeek-r1-distill-qwen-1.5B** optimized for **Intel NPUs** with [nexaSDK](https://sdk.nexa.ai).

## Quickstart

1. **Install nexaSDK** and create a free account at [sdk.nexa.ai](https://sdk.nexa.ai)
2. **Activate your device** with your access token:

   ```bash
   nexa config set license '<access_token>'
   ```
3. Run the model on NPU in one line:

   ```bash
   nexa infer NexaAI/deepSeek-r1-distill-qwen-1.5B-intel-npu
   ```

## Model Description
**deepSeek-r1-distill-qwen-1.5B** is a distilled variant of DeepSeek-R1, built on the Qwen-1.5B architecture.  
It compresses the reasoning and instruction-following capabilities of larger DeepSeek models into an ultra-lightweight 1.5B parameter model—ideal for fast, efficient deployment on constrained devices while retaining strong performance for its size.

## Features
- **Distilled from DeepSeek-R1**: Maintains core reasoning and comprehension strengths in a smaller model.  
- **Instruction-tuned**: Optimized for Q&A, task completion, and logical reasoning.  
- **Compact footprint**: 1.5B parameters enable deployment in edge and mobile contexts.  
- **Multilingual support**: Handles a wide range of global languages with efficiency.

## Use Cases
- Lightweight conversational agents and personal assistants.  
- Coding help and small-scale algorithmic reasoning.  
- Multilingual Q&A or translation in resource-limited environments.  
- Edge, mobile, and offline applications where compute or memory is limited.

## Inputs and Outputs
**Input**: Text prompts including natural language queries, tasks, or code snippets.  
**Output**: Direct responses—answers, explanations, or code—without extra reasoning annotations.

## License
- Licensed under **Apache-2.0**

## References
- Model card: [https://huggingface.co/deepseek-ai/deepseek-r1-distill-qwen-1.5b](https://huggingface.co/deepseek-ai/deepseek-r1-distill-qwen-1.5b)