---
license: agpl-3.0
library_name: coreml
pipeline_tag: object-detection
tags:
  - coreml
  - core-ml
  - ios
  - macos
  - apple
  - on-device
  - yolo
  - real-time
  - nms-free
  - arxiv:2405.14458
---

# YOLOv10n — Core ML

*Object Detection, 2024*

YOLOv10 nano. 640×640 input. Dual-assignment strategy.

Core ML conversion of [THU-MIG/yolov10](https://github.com/THU-MIG/yolov10) for on-device inference on iPhone, iPad and Mac. Converted with `coremltools`; the packages are stateless, so all sequencing and buffering lives in your Swift code.

| | |
|---|---|
| Task | object detection |
| Upstream | [THU-MIG/yolov10](https://github.com/THU-MIG/yolov10) |
| Packages | 1 |
| Download size | 4 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~300 MB |

## Files

| File | Size | Compute units | SHA-256 |
|---|---:|---|---|
| `YOLOv10N.mlpackage.zip` | 4 MB | `all` | `9a687144a6b0b764…` |
| **Total** | **4 MB** | | |

`compute_units` is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU.

## Download

```bash
hf download mlboydaisuke/coreml-zoo --include "yolov10/*" --local-dir ./yolov10n
unzip './yolov10n/yolov10/*.zip' -d ./yolov10n
```

## Use in Swift

```swift
import CoreML

let config = MLModelConfiguration()
config.computeUnits = .all   // as converted — see the table above

// Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it
// at build time:
let model = try YOLOv10N(configuration: config)

// ...or compile a downloaded .mlpackage at runtime:
let compiled = try await MLModel.compileModel(at: mlpackageURL)
let model = try MLModel(contentsOf: compiled, configuration: config)
```

## Demo

- **Sample app** — [`sample_apps/YOLOv10Demo`](https://github.com/john-rocky/CoreML-Models/tree/master/sample_apps/YOLOv10Demo), a standalone SwiftUI project.
- **Models Zoo** — this model is downloadable and runnable inside the [Models Zoo app](https://apps.apple.com/app/id6762083207) on the App Store, no build required.

## Conversion

- Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling): [`docs/coreml_conversion_notes.md`](https://github.com/john-rocky/CoreML-Models/blob/master/docs/coreml_conversion_notes.md)
- Model index: [CoreML-Models](https://github.com/john-rocky/CoreML-Models)

## License

The conversion inherits the upstream license: **AGPL-3.0**.

## Credits

- Upstream authors: [THU-MIG/yolov10](https://github.com/THU-MIG/yolov10), 2024
- Core ML conversion: john-rocky (Daisuke Majima)