--- title: Phi-4-Mini-Instruct canonical_url: "https://www.modelscope.cn/models/Qualcomm-AI-Hub/Phi-4-Mini-Instruct" md_url: "https://www.modelscope.cn/models/Qualcomm-AI-Hub/Phi-4-Mini-Instruct.md" repository: Qualcomm-AI-Hub/Phi-4-Mini-Instruct last_updated: 2026-10-16 license: mit pipeline_tag: text-generation tasks: - text-generation downloads: 0 stars: 0 tags: - llm - generative_ai - android --- # Phi-4-Mini-Instruct > Phi-4-Mini-Instruct - Qualcomm-AI-Hub 在 ModelScope 开源的模型。Phi-4-Mini-Instruct: Optimized for Qualcomm Devices Qualcomm-AI-Hub/Phi-4-Mini-Instruct 是 ModelScope 魔搭社区上的text-generation模型，采用 mit 许可。 - **Repository**: Qualcomm-AI-Hub/Phi-4-Mini-Instruct - **License**: mit - **Tasks**: text-generation - **Tags**: llm, generative_ai, android - **Downloads**: 0 - **Stars**: 0 - **Last updated**: 2026-10-16 Source: https://www.modelscope.cn/models/Qualcomm-AI-Hub/Phi-4-Mini-Instruct --- ![](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/phi_4_mini_instruct/web-assets/model_demo.png) # Phi-4-Mini-Instruct: Optimized for Qualcomm Devices Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. This is based on the implementation of Phi-4-Mini-Instruct found [here](https://huggingface.co/microsoft/Phi-4-mini-instruct). This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/phi_4_mini_instruct) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary). Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.cn) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device. ## Deploying Phi-4-Mini-Instruct on-device Follow the [GenieX quickstart](https://geniex.aihub.qualcomm.com/en/get-started/quickstart) to install GenieX and deploy the model on a target device. ## Getting Started There are two ways to deploy this model on your device: ### Option 1: Download Pre-Exported Models Below are pre-exported model assets ready for deployment. | Runtime | Precision | Chipset | SDK Versions | Download | |---|---|---|---|---| | GENIEX_LLAMACPP | q4_0 | Universal | | [Download](https://huggingface.co/bartowski/microsoft_Phi-4-mini-instruct-GGUF/resolve/main/microsoft_Phi-4-mini-instruct-Q4_0.gguf) For more device-specific assets and performance metrics, visit **[Phi-4-Mini-Instruct on Qualcomm® AI Hub](https://aihub.qualcomm.cn/models/phi_4_mini_instruct)**. ### Option 2: Export with Custom Configurations Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/phi_4_mini_instruct) Python library to compile and export the model with your own: - Custom weights (e.g., fine-tuned checkpoints) - Custom input shapes - Target device and runtime configurations This option is ideal if you need to customize the model beyond the default configuration provided here. See our repository for [Phi-4-Mini-Instruct on GitHub](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/phi_4_mini_instruct) for usage instructions. ## Model Details **Model Type:** Model_use_case.text_generation **Model Stats:** - Number of parameters: 3.8B - Response Rate: Rate of response generation after the first response token. - TTFT: Time To First Token is the time it takes to generate the first response token. This is expressed as a range because it varies based on the length of the prompt. The lower bound is for a short prompt (up to 128 tokens, i.e., one iteration of the prompt processor) and the upper bound is for a prompt using the full context length (4096 tokens). ## Performance Summary | Model | Runtime | Precision | Chipset | Context Length | Response Rate (tokens per second) | Time To First Token (range, seconds) |---|---|---|---|---|---|--- | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 512 | 23.230486 | 3.538779 - 14.155116 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 512 | 20.216085 | 1.514717 - 6.058868 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 512 | 18.990644 | 0.35408999999999996 - 1.4163599999999998 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 4096 | 9.043983 | 72.060935 - 2305.94992 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 4096 | 11.167019 | 29.135119 - 932.323808 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 4096 | 14.313395 | 5.057653 - 161.844896 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 512 | 24.055461 | 0.9468802500000001 - 3.7875210000000004 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 512 | 23.939526 | 0.95809125 - 3.832365 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 512 | 19.557942 | 0.1830165 - 0.732066 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 4096 | 13.965758 | 1.94027484375 - 62.088795 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 4096 | 8.177678 | 2.3551633124999998 - 75.36522599999999 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 4096 | 13.116693 | 0.35286768749999997 - 11.291765999999999 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 512 | 34.223958 | 1.015909 - 4.063636 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 512 | 28.03951 | 0.813092 - 3.252368 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 512 | 26.878243 | 0.30885199999999996 - 1.2354079999999998 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 4096 | 22.358129 | 14.089633 - 450.868256 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 4096 | 21.080379 | 11.711404 - 374.764928 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 4096 | 18.123052 | 3.209757 - 102.712224 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 512 | 27.988389 | 0.40832025 - 1.633281 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 512 | 27.143556 | 0.46132475 - 1.845299 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 512 | 16.042448 | 0.25184725 - 1.007389 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 4096 | 15.617096 | 0.913791375 - 29.241324 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 4096 | 16.000366 | 0.9590768749999999 - 30.690459999999998 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 4096 | 9.673267 | 0.41174053125 - 13.175697 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-8275 | 512 | 4.552376 | 12.93992 - 51.75968 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-8275 | 512 | 2.596201 | 18.429702000000002 - 73.71880800000001 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-8275 | 512 | 9.976684 | 1.089346 - 4.357384 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-8275 | 4096 | 1.597252 | 140.87717800000001 - 4508.0696960000005 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-8275 | 4096 | 1.921158 | 213.723029 - 6839.136928 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-8275 | 4096 | 6.191769 | 10.702895 - 342.49264 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-X7181 | 512 | 27.988389 | 0.40832025 - 1.633281 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-X7181 | 512 | 27.143556 | 0.46132475 - 1.845299 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-X7181 | 512 | 16.042448 | 0.25184725 - 1.007389 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ Q-8750 | 512 | 24.055461 | 0.9468802500000001 - 3.7875210000000004 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ Q-8750 | 512 | 23.939526 | 0.95809125 - 3.832365 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ Q-8750 | 512 | 19.557942 | 0.1830165 - 0.732066 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-9075 | 4096 | 13.1 | 1.9971918880000001 - 63.91014 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-9075 | 4096 | 3.0 | 2.471042471 - 79.073359 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-9075 | 4096 | 10.0 | 0.44137930999999997 - 14.124138 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-X7181 | 4096 | 15.617096 | 0.913791375 - 29.241324 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-X7181 | 4096 | 16.000366 | 0.9590768749999999 - 30.690459999999998 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ IQ-X7181 | 4096 | 9.673267 | 0.41174053125 - 13.175697 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ Q-8750 | 4096 | 13.965758 | 1.94027484375 - 62.088795 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ Q-8750 | 4096 | 8.177678 | 2.3551633124999998 - 75.36522599999999 | Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Qualcomm® Dragonwing™ Q-8750 | 4096 | 13.116693 | 0.35286768749999997 - 11.291765999999999 ## License * The license for the original implementation of Phi-4-Mini-Instruct can be found [here](https://huggingface.co/microsoft/Phi-4-mini-instruct/blob/main/LICENSE). ## References * [Phi-4 Technical Report](https://arxiv.org/abs/2412.08905) * [Source Model Implementation](https://huggingface.co/microsoft/Phi-4-mini-instruct) ## Community * For questions or feedback, chat with our engineers in [Qualcomm® AI Hub Workbench](https://workbench.aihub.qualcomm.cn). ## Usage and Limitations This model may not be used for or in connection with any of the following applications: - Accessing essential private and public services and benefits; - Administration of justice and democratic processes; - Assessing or recognizing the emotional state of a person; - Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics; - Education and vocational training; - Employment and workers management; - Exploitation of the vulnerabilities of persons resulting in harmful behavior; - General purpose social scoring; - Law enforcement; - Management and operation of critical infrastructure; - Migration, asylum and border control management; - Predictive policing; - Real-time remote biometric identification in public spaces; - Recommender systems of social media platforms; - Scraping of facial images (from the internet or otherwise); and/or - Subliminal manipulation