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This demo runs the MiniCPM-V family of multimodal models fully on-device on iOS, Android, and HarmonyOS NEXT. Three model versions are currently supported:
- MiniCPM-V 2.6
- MiniCPM-V 4.0
- MiniCPM-V 4.6
This repository contains three on-device demos for MiniCPM-V (multimodal LLM) running fully locally via llama.cpp:
MiniCPM-V-demo/— iOS demo (Xcode project)MiniCPM-V-demo-Android/— Android demo (Gradle / Kotlin)MiniCPM-V-demo-HarmonyOS/— HarmonyOS NEXT demo (DevEco Studio / ArkTS)
All three demos share the same llama.cpp submodule (branch MiniCPM-V) at the repo root.
NOTE: This project bundles
llama.cppas a git submodule. The upstream forktc-mb/llama.cppcarries a dozen unrelated branches and a full clone weighs ~350 MB, soshallow = trueis set in.gitmodulesby default. The recommended shallow + single-branch clone is:# one-shot (parent repo + submodules, all shallow) git clone --recurse-submodules --shallow-submodules \ https://github.com/OpenBMB/MiniCPM-V-Apps.git cd MiniCPM-V-AppsOr, if you've already cloned the parent repo and want to init the submodule afterwards:
git submodule update --init --recursive --depth 1 --single-branchThis only pulls a single commit of the
MiniCPM-Vbranch (~tens of MB) instead of the full llama.cpp fork history. Developers who need to push totc-mb/llama.cpp:MiniCPM-Vcan rungit fetch --unshallowinside the submodule to lift the shallow restriction.
The README is organised in two parts:
- Part 1 — Platform setup: how to build and run the demo on iOS, Android and HarmonyOS.
- Part 2 — GGUF model files: where to get the model weights for each MiniCPM-V version, and the minimum on-device hardware needed to run them.
Just want to install the app? Pre-built TestFlight (iOS) / APK (Android) / HAP (HarmonyOS) packages and step-by-step install instructions are in DOWNLOAD.md. The rest of this README is only needed if you want to build from source.
NOTE: To deploy and test the app on an iOS device, you may need an Apple Developer account.
-
Download Xcode from the App Store (verified on Xcode 26.1; project deployment target = iOS 16.4)
-
Install the Command Line Tools:
xcode-select --install
-
Agree to the software license agreement:
sudo xcodebuild -license
-
CMake ≥ 3.28 (needed by the xcframework build in the next step):
brew install cmake
This repo does not track any compiled artefacts, so the prebuilt llama.xcframework (~189 MB) needs to be produced locally from the llama.cpp submodule and dropped into MiniCPM-V-demo/thirdparty/ for Xcode to link against. A one-shot script is provided — by default it only builds the two slices the demo actually links (real device + simulator), which takes ~2-3 min on a modern M-series Mac:
./scripts/build_xcframework.shThe output is installed at MiniCPM-V-demo/thirdparty/llama.xcframework/.
If you need a different build scope (simulator-only, full multi-platform, …), the script forwards MINIMAL_MODE:
MINIMAL_MODE=ios-sim ./scripts/build_xcframework.sh # simulator only (~3 min)
MINIMAL_MODE=ios-device ./scripts/build_xcframework.sh # device only (~3 min)
MINIMAL_MODE=ios ./scripts/build_xcframework.sh # device + simulator (default, ~3 min)
MINIMAL_MODE=all ./scripts/build_xcframework.sh # iOS + macOS + tvOS + xrOS (~25 min)The equivalent manual commands, if you'd rather not use the script:
cd llama.cpp
MINIMAL_MODE=ios ./build-xcframework.sh
cp -r ./build-apple/llama.xcframework ../MiniCPM-V-demo/thirdparty/During the build you will see warnings like ignoring duplicate libraries and skipping debug map object with duplicate name and timestamp — these come from llama.cpp's mtmd module having identically-named .o files across different model architectures. They are harmless and the resulting framework works correctly.
When do I need to rebuild?
- The parent repo bumped the llama.cpp submodule pointer (
git submodule statusshows a commit different from your last local build).- You edited any source under
llama.cpp/that affects the framework.
Open MiniCPM-V-demo/MiniCPM-V-demo.xcodeproj with Xcode. It may take a moment for Xcode to automatically download the required dependencies. Select the target device at the top, then click the "Run" (triangle) button to launch the demo.
If Xcode fails with There is no XCFramework found at '.../llama.xcframework', you skipped §1.1.2 — go back and run the build.
Requirements:
- Android Studio (Giraffe or newer)
- Android SDK + NDK (the project pins NDK
28.2.13676358and CMake3.22.1) - A physical device with a 64-bit ARM SoC (
arm64-v8a) - Device RAM: see the per-model requirements in Part 2
Build & run:
cd MiniCPM-V-demo-Android
./gradlew assembleDebugOr open MiniCPM-V-demo-Android/ directly in Android Studio and click Run.
The first launch will download the GGUF model files into the app's external storage. You can also sideload model files manually via adb push — see in-app Model Manager for the expected directory layout.
Requirements:
- DevEco Studio 5.0 or newer (with the HarmonyOS Native SDK / NDK)
- A real device or emulator running HarmonyOS API 12+ (e.g. nova 14 vitality / Mate 60 / Pura 70)
- 64-bit ARM architecture (
arm64-v8a) - Device RAM: see the per-model requirements in Part 2
Build & run:
- Open
MiniCPM-V-demo-HarmonyOS/in DevEco Studio. File→Project Structure→Signing Configsand tick Automatically generate signature (requires a Huawei developer account; this only needs to be done once).- Connect the device with USB debugging enabled, then click Run (the green triangle).
After the first launch, open the in-app Model Manager and tap Download. You can also sideload model files via hdc file send; see MiniCPM-V-demo-HarmonyOS/README_zh.md for the expected directory layout.
The HarmonyOS port shares the exact same
llama.cppsubmodule, model catalogue, OBS direct-link URLs and MD5 hashes with the iOS / Android demos.
The on-device memory needed to run a model is roughly (model file size) + KV cache + a few hundred MB of working memory for the vision encoder and llama.cpp internals. The recommended values below leave enough headroom for the OS and the demo app itself.
| Model | LLM params | Recommended quant | LLM file (Q4) | mmproj (f16) | Total download | Recommended device RAM |
|---|---|---|---|---|---|---|
| MiniCPM-V 2.6 | 8B | Q4_K_M | ~4.4 GB | ~1.0 GB | ~5.4 GB | ≥ 8 GB |
| MiniCPM-V 4.0 | 4.1B | Q4_K_M | ~2.0 GB | ~0.9 GB | ~2.9 GB | ≥ 6 GB |
| MiniCPM-V 4.6 | 1.3B | Q4_K_M | ~0.5 GB | ~1.1 GB | ~1.6 GB | ≥ 6 GB |
Notes:
mmprojis the vision projector + ViT weights; it is shipped in f16 because quantising the visual tower hurts perception quality noticeably more than quantising the LLM.- All three demos default to a context window of 4K tokens. Larger contexts will increase the KV-cache footprint roughly linearly, so on a borderline device you may need to lower it.
- On Android / HarmonyOS, devices with 8 GB+ RAM are strongly recommended for V 2.6. On iOS, V 2.6 has been validated on iPhone 15 Pro / 16 series and recent iPads with M-series chips; older 6 GB devices may swap heavily.
- HuggingFace: https://huggingface.co/openbmb/MiniCPM-V-2_6-gguf
- ModelScope: https://modelscope.cn/models/OpenBMB/MiniCPM-V-2_6-gguf
Download the language model file (e.g., ggml-model-Q4_0.gguf) and the vision model file (mmproj-model-f16.gguf) from the repository.
- HuggingFace: https://huggingface.co/openbmb/MiniCPM-V-4-gguf
- ModelScope: https://modelscope.cn/models/OpenBMB/MiniCPM-V-4-gguf
Download the language model file (e.g., ggml-model-Q4_K_M.gguf) and the vision model file (mmproj-model-f16.gguf) from the repository.
- HuggingFace: https://huggingface.co/openbmb/MiniCPM-V-4.6-gguf
- ModelScope: https://modelscope.cn/models/OpenBMB/MiniCPM-V-4.6-gguf
Download the language model file (e.g., MiniCPM-V-4_6-Q4_K_M.gguf) and the vision model file (mmproj-model-f16.gguf) from the repository.