---
title: macOS Support
sidebar_position: 18
slug: /deployment-macos-support
---

# macOS Support Matrix

Langflow supports both Apple Silicon (ARM64) and Intel (x86_64) Macs, but with different feature availability due to hardware capabilities and upstream dependency support.

## Quick Reference

| Feature Category | Apple Silicon (M1/M2/M3) | Intel (x86_64) |
|-----------------|--------------------------|----------------|
| **Core Langflow** | ✅ Full support | ✅ Full support |
| **ML/AI Components** | ✅ Full support | ❌ Limited/Unavailable |
| **GPU Acceleration** | ✅ Metal support | ❌ Not available |
| **Native OCR** | ✅ Full support | ✅ Full support |

## Detailed Feature Support

### Core Functionality (Both Architectures)

The following features work on **both Apple Silicon and Intel Macs**:

- ✅ Flow builder and visual editor
- ✅ API server and endpoints
- ✅ Database operations (SQLite, PostgreSQL)
- ✅ Authentication and user management
- ✅ All non-ML components (text processing, API calls, data transformations)
- ✅ Native OCR via `ocrmac` (uses macOS Vision framework)
- ✅ Vector stores and embeddings (when using API-based providers)
- ✅ LangChain integrations (non-ML components)

### ML/AI Features (Apple Silicon Only)

The following features require **Apple Silicon (ARM64)** and are **not available on Intel Macs**:

#### ❌ Not Available on Intel

- **ALTK (Agent Lifecycle Toolkit)** - Requires PyTorch
- **HuggingFace Transformers** - Requires PyTorch
- **Sentence Transformers** - Requires PyTorch
- **EasyOCR** - Requires PyTorch
- **Docling (binary processing)** - Requires PyTorch
  - Note: `docling-core` (metadata-only) works on Intel
- **MLX and MLX-VLM** - Apple Silicon exclusive framework
- **Metal GPU acceleration** - Requires Apple Silicon hardware
- **CUGA** - Apple Silicon only

## Why the Difference?

### PyTorch Deprecation

PyTorch dropped support for macOS Intel (x86_64) starting with version 2.3.0 (April 2024). The last version with Intel Mac support was PyTorch 2.2.2, which only supports Python 3.10-3.12.

Since many ML components depend on PyTorch, they are automatically excluded on Intel Macs to prevent installation failures.

### Hardware Limitations

Intel Macs lack the specialized hardware that makes ML workloads performant:
- No Neural Engine
- No Metal 3 GPU acceleration
- Limited memory bandwidth compared to Apple Silicon's unified memory architecture

## Installation Recommendations

### For Apple Silicon Users

Install Langflow normally with all features:

```bash
pip install langflow
```

Or with specific ML extras:

```bash
pip install langflow[altk,langchain-huggingface,easyocr]
```

### For Intel Mac Users

Install the base package for core functionality:

```bash
pip install langflow
```

**Note:** Attempting to install ML-dependent extras on Intel Macs will be automatically skipped due to platform markers in the package configuration.

## Python Version Support

| Python Version | Apple Silicon | Intel Mac |
|---------------|---------------|-----------|
| 3.10 | ✅ Supported | ✅ Supported |
| 3.11 | ✅ Supported | ✅ Supported |
| 3.12 | ✅ Supported | ✅ Supported |
| 3.13 | ✅ Supported | ⚠️ Limited (no PyTorch) |
| 3.14 | ✅ Supported | ⚠️ Limited (no PyTorch) |

:::note
Python 3.13+ on Intel Macs cannot use PyTorch-dependent features due to the lack of PyTorch wheels for macOS x86_64. This affects ML components like ALTK, HuggingFace, EasyOCR, and Docling.
:::

## Workarounds for Intel Mac Users

If you need ML features on an Intel Mac, consider these alternatives:

### 1. Use API-Based Providers

Instead of local models, use API-based services:
- OpenAI API for embeddings and completions
- Cohere API for embeddings
- Anthropic API for Claude models
- HuggingFace Inference API

### 2. Remote Inference

Run ML workloads on a remote server:
- Deploy Langflow on a cloud instance with GPU support
- Use the Langflow API to connect from your Intel Mac
- Keep the UI/development on your Mac, inference in the cloud

### 3. Docker with Rosetta 2

For some workloads, you can use Docker with ARM64 images via Rosetta 2:

```bash
docker run --platform linux/arm64 langflowai/langflow:latest
```

**Note:** Performance will be slower than native, and not all features may work correctly.

## Future Support

### Intel Mac Deprecation Timeline

Apple and the broader ecosystem are phasing out Intel Mac support:

- **2022:** Last Intel MacBook Pro shipped
- **2024:** PyTorch dropped Intel Mac support
- **2026-2027:** Expected end of macOS updates for Intel Macs

Langflow will continue to support core functionality on Intel Macs as long as Python and essential dependencies remain available, but ML features will remain Apple Silicon exclusive.

### Recommended Migration Path

If you rely on ML features, consider upgrading to Apple Silicon hardware:
- M1/M2/M3 MacBook Air (cost-effective)
- M1/M2/M3 MacBook Pro (for intensive workloads)
- Mac Mini with M2/M3 (desktop option)

## Troubleshooting

### "No matching distribution found" Errors

If you see errors about missing packages on Intel Mac:

1. **Expected behavior** - ML packages are intentionally excluded
2. **Solution** - Use core Langflow features or API-based alternatives
3. **Verify architecture:**
   ```bash
   python -c "import platform; print(platform.machine())"
   # x86_64 = Intel, arm64 = Apple Silicon
   ```

### Performance Issues

If Langflow feels slow on Intel Mac:

1. Ensure you're not trying to run ML workloads locally
2. Use API-based providers for embeddings/completions
3. Consider upgrading to Apple Silicon for better performance

## Related Documentation

- [Deployment Overview](/deployment-overview)
- [Docker Deployment](/deployment-docker)
- [Production Best Practices](/deployment-prod-best-practices)

## Need Help?

If you have questions about macOS support:

- [GitHub Discussions](https://github.com/langflow-ai/langflow/discussions)
- [Discord Community](https://discord.gg/EqksyE2EX9)
- [Documentation](https://docs.langflow.org)