build: add support for python 3.14

.ci/scripts/test_coreml_bc.sh

@@ -21,7 +21,7 @@ REPO_ROOT="${1:-$(pwd)}"
 source "${REPO_ROOT}/.ci/scripts/utils.sh"
 
 # Create a conda environment with Python 3.10 for compatibility with old ET versions
-# ET 1.0.0 only supports Python >=3.10,<3.13
+# ET 1.0.0 only supports Python >=3.10,<3.15
 CONDA_ENV_NAME="coreml_bc_test_env"
 conda create -y -n "${CONDA_ENV_NAME}" python=3.10 pip packaging
 

.claude/skills/building/SKILL.md

@@ -23,17 +23,17 @@ conda activate executorch
 
 **Path B — no conda (fall back to venv):**
 ```bash
-# Find a compatible Python (3.10–3.13). On macOS with only Homebrew Python 3.14+,
+# Find a compatible Python (3.10–3.14). On macOS with only Homebrew Python 3.14+,
 # install a compatible version first: brew install python@3.12
-python3.12 -m venv .executorch-venv   # or python3.11, python3.10, python3.13
+python3.12 -m venv .executorch-venv   # or python3.11, python3.10, python3.13, python3.14
 source .executorch-venv/bin/activate
 pip install --upgrade pip
 ```
 
 **Then verify (either path):**
 
 Run `python --version` and `cmake --version`. Fix automatically:
-- **Python not 3.10–3.13**: recreate the env with a correct Python version.
+- **Python not 3.10–3.14**: recreate the env with a correct Python version.
 - **cmake missing or < 3.24**: run `pip install 'cmake>=3.24'` inside the env.
 - **cmake >= 4.0**: works in practice, no action needed.
 

.github/workflows/build-wheels-aarch64-linux.yml

@@ -30,7 +30,7 @@ jobs:
       test-infra-ref: main
       with-cuda: disabled
       with-rocm: disabled
-      python-versions: '["3.10", "3.11", "3.12", "3.13"]'
+      python-versions: '["3.10", "3.11", "3.12", "3.13", "3.14"]'
 
   build:
     needs: generate-matrix

.github/workflows/build-wheels-linux.yml

@@ -30,7 +30,7 @@ jobs:
       test-infra-ref: main
       with-cuda: disabled
       with-rocm: disabled
-      python-versions: '["3.10", "3.11", "3.12", "3.13"]'
+      python-versions: '["3.10", "3.11", "3.12", "3.13", "3.14"]'
 
   build:
     needs: generate-matrix

.github/workflows/build-wheels-macos.yml

@@ -30,7 +30,7 @@ jobs:
       test-infra-ref: main
       with-cuda: disabled
       with-rocm: disabled
-      python-versions: '["3.10", "3.11", "3.12", "3.13"]'
+      python-versions: '["3.10", "3.11", "3.12", "3.13", "3.14"]'
 
   build:
     needs: generate-matrix

.github/workflows/build-wheels-windows.yml

@@ -33,7 +33,7 @@ jobs:
       test-infra-ref: main
       with-cuda: disabled
       with-rocm: disabled
-      python-versions: '["3.10", "3.11", "3.12", "3.13"]'
+      python-versions: '["3.10", "3.11", "3.12", "3.13", "3.14"]'
 
   build:
     needs: generate-matrix

.github/workflows/pull.yml

@@ -43,7 +43,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [ "3.10", "3.11", "3.12", "3.13" ]
+        python-version: [ "3.10", "3.11", "3.12", "3.13", "3.14" ]
     with:
       runner: linux.2xlarge
       docker-image: ci-image:executorch-ubuntu-22.04-qnn-sdk

README-wheel.md

@@ -5,7 +5,7 @@ ExecuTorch is to enable wider customization and deployment capabilities of the
 PyTorch programs.
 
 The `executorch` pip package is in beta.
-* Supported python versions: 3.10, 3.11, 3.12, 3.13
+* Supported python versions: 3.10, 3.11, 3.12, 3.13, 3.14
 * Compatible systems: Linux x86_64, Linux aarch64, macOS aarch64
 
 To build a minimal wheel from source, set

docs/source/getting-started.md

@@ -8,7 +8,7 @@ This section is intended to describe the necessary steps to take a PyTorch model
 ## System Requirements
 The following are required to install the ExecuTorch host libraries, needed to export models and run from Python. Requirements for target end-user devices are backend dependent. See the appropriate backend documentation for more information.
 
-- Python 3.10 - 3.13
+- Python 3.10 - 3.14
 - g++ version 7 or higher, clang++ version 5 or higher, or another C++17-compatible toolchain.
 - Linux (x86_64 or ARM64), macOS (ARM64), or Windows (x86_64).
     - Intel-based macOS systems require building PyTorch from source (see [Building From Source](using-executorch-building-from-source.md) for instructions).

docs/source/pathway-beginner.md

@@ -65,7 +65,7 @@ Install ExecuTorch and verify your setup before attempting to export a model.
 
 Install the ExecuTorch Python package, export a MobileNet V2 model using XNNPACK, and run your first inference. This is the canonical entry point for all new users.
 
-**Difficulty:** Beginner | **Prerequisites:** Python 3.10–3.13, PyTorch, g++7+ or clang5+
+**Difficulty:** Beginner | **Prerequisites:** Python 3.10–3.14, PyTorch, g++7+ or clang5+
 :::
 
 ::::

docs/source/pathway-quickstart.md

@@ -66,7 +66,7 @@ Follow the {doc}`llm/llama` guide for the complete Llama export and deployment w
 
 ## The 5-Minute Setup
 
-If you have not yet installed ExecuTorch, run the following in a Python 3.10–3.13 virtual environment:
+If you have not yet installed ExecuTorch, run the following in a Python 3.10–3.14 virtual environment:
 
 ```bash
 pip install executorch

docs/source/quick-start-section.md

@@ -52,7 +52,7 @@ Follow these guides in order to get started with ExecuTorch:
 
 ## Prerequisites
 
-- Python 3.10–3.13
+- Python 3.10–3.14
 - PyTorch 2.9+
 - Basic familiarity with PyTorch model development
 

docs/source/raspberry_pi_llama_tutorial.md

@@ -4,7 +4,7 @@
 
 This tutorial demonstrates how to deploy **Llama models on Raspberry Pi 4/5 devices** using ExecuTorch:
 
-- **Prerequisites**: Linux host machine, Python 3.10-3.13, conda environment, Raspberry Pi 4/5
+- **Prerequisites**: Linux host machine, Python 3.10-3.14, conda environment, Raspberry Pi 4/5
 - **Setup**: Automated cross-compilation using `setup.sh` script for ARM toolchain installation
 - **Export**: Convert Llama models to optimized `.pte` format with quantization options
 - **Deploy**: Transfer binaries to Raspberry Pi and configure runtime libraries
@@ -19,7 +19,7 @@ This tutorial demonstrates how to deploy **Llama models on Raspberry Pi 4/5 devi
 
 **Software Dependencies**:
 
-- **Python 3.10-3.13** (ExecuTorch requirement)
+- **Python 3.10-3.14** (ExecuTorch requirement)
 - **conda** or **venv** for environment management
 - **CMake 3.29.6+**
 - **Git** for repository cloning
@@ -42,7 +42,7 @@ uname -s  # Should output: Linux
 uname -m  # Should output: x86_64
 
 # Check Python version
-python3 --version  # Should be 3.10-3.13
+python3 --version  # Should be 3.10-3.14
 
 # Check required tools
 hash cmake git md5sum 2>/dev/null || echo "Missing required tools"

docs/source/using-executorch-building-from-source.md

@@ -28,7 +28,7 @@ ExecuTorch is tested on the following systems, although it should also work in s
   - Otherwise, Python's built-in virtual environment manager `python venv` is a good alternative.
 * `g++` version 7 or higher, `clang++` version 5 or higher, or another
   C++17-compatible toolchain.
-* `python` version 3.10-3.13
+* `python` version 3.10-3.14
 * `ccache` (optional) - A compiler cache that speeds up recompilation
 * **macOS**
   - `Xcode Command Line Tools`

pyproject.toml

@@ -51,9 +51,10 @@ classifiers = [
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
 ]
 
-requires-python = ">=3.10,<3.14"
+requires-python = ">=3.10,<3.15"
 
 # Runtime dependencies are declared dynamically (see `dynamic` above) and
 # computed in setup.py, so the EXECUTORCH_BUILD_MINIMAL wheel can ship a slimmer
@@ -151,4 +152,4 @@ wrap-summaries = 80
 wrap-descriptions = 80
 style = "sphinx"
 close-quotes-on-newline = true
-blank = true
+blank = true