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System Requirements

This page separates declared compatibility from capacity planning. The first is enforced by package metadata and release builds. The second is practical guidance for choosing hardware; it is not a claim that every workload was benchmarked on exactly that configuration.

Supported Software

Component Requirement Notes
Python SDK Python 3.10 through 3.14 Python 3.15 is not supported by the current package metadata.
Operating system 64-bit Windows, macOS, or Linux The Python package is cross-platform; availability of optional scientific wheels can differ by OS and CPU architecture.
Linux desktop beta x86_64 Linux The current AppImage is built on Ubuntu 22.04 and is not an ARM AppImage.
Windows desktop beta Windows x64 Distributed as an .exe installer.
macOS desktop beta macOS build from the current GitHub macos-latest runner The beta is not advertised as a universal binary; inspect the release notes when CPU architecture matters.
Internet access Required for initial installation Also required for public biological APIs, Hugging Face downloads, Ollama model pulls, and update checks. Simulations can run offline after dependencies and inputs are present.
User storage Writable home and output directories The SDK writes environments, caches, run bundles, reports, models, and datasets outside the source tree when configured to do so.

No GPU is required for ordinary simulation, validation, MDMP certification, or report generation.

Capacity Planning

These figures are conservative starting points. Study duration, cohort size, report resolution, dataset size, model size, and parallelism can increase demand substantially.

Workload Practical minimum Recommended Free storage to reserve
CLI, small simulations, validation 2 CPU cores, 4 GB RAM 4 CPU cores, 8 GB RAM 2-5 GB
Reports and desktop workbench 4 CPU cores, 8 GB RAM 4-8 CPU cores, 16 GB RAM 5-10 GB
Local Ollama explanation with a small model 4 CPU cores, 8 GB RAM 8 CPU cores or supported GPU, 16 GB RAM 10-30 GB
Glucose-model training and large study matrices 8 CPU cores, 16 GB RAM 8+ CPU cores, 32 GB RAM, optional supported GPU 25-100+ GB
Long-running Jetson or edge research board-specific active cooling and monitored storage depends on checkpoints and telemetry

Storage estimates exclude private datasets, Ollama models, model checkpoints, exported figures, and accumulated results/ folders. Those artifacts usually dominate long-term storage.

Installation Profiles

Profile Python package Main use
Standard iints-sdk-python35[full,mdmp] simulation, reports, imports, and certification
Research iints-sdk-python35[full,mdmp,research] Torch, ONNX, Parquet/HDF5, and interactive research plots
Edge iints-sdk-python35[edge,mdmp] serial bridges and supported hardware workflows
Maintained desktop engine iints-sdk-python35[tauri-engine] Tauri/Python bridge, reports, interactive plots, SBML, and FMI support
Legacy Qt/development bundle iints-sdk-python35[desktop-all] compatibility testing for the former PySide interface plus ML/packaging dependencies

The research and legacy desktop-all profiles are much larger because they include machine-learning or GUI-packaging libraries. The maintained app uses the smaller tauri-engine profile; install a training profile only on machines that actually train models.

External Tools

The following tools are optional and are not silently installed with the normal SDK package:

  • Ollama and its model files
  • COPASI
  • OpenCOR
  • external FMUs used through FMPy
  • private or licensed datasets
  • pretrained Hugging Face model weights

The desktop workbench detects missing optional tools and should keep unrelated workflows available.

Desktop-Specific Notes

The Linux AppImage bundles the application shell, but the scientific Python engine remains a private environment under ~/.iints-af/python-engine. On Omarchy, the supported installer prepares both layers and installs fuse2 for normal AppImage startup.

Tauri documents that AppImage compatibility depends on the GNU C Library baseline used for the build. The IINTS-AF Linux beta is built on Ubuntu 22.04, while current rolling-release Omarchy systems provide a newer userspace. See the Tauri AppImage guide for the underlying compatibility model.

Check A Machine

Before installing:

=== "Linux or macOS"

```bash
uname -m
python3 --version
python3 -c "import platform; print(platform.platform())"
df -h "$HOME"
```

=== "Windows PowerShell"

```powershell
py --version
Get-CimInstance Win32_OperatingSystem | Select-Object OSArchitecture, TotalVisibleMemorySize
Get-PSDrive -PSProvider FileSystem
```

After installing:

iints --version
iints version --refresh
iints doctor --smoke-run --suggest

Use iints doctor --full --suggest before a long study, edge deployment, or AI workflow.

Platform Guides

Basis For These Requirements

Last reviewed: 2026-08-22.