Why Loom vs the rest of AI
Cloud chatbots rent intelligence. PyTorch rents a Python runtime. Loom is a pure Go AI engine you embed—offline, deterministic, Apache 2.0—with a shipped app (SoulGlitch) that proves it on real phones.
The OpenFluke stack
Not a single API—an open-source AI infrastructure lab: engine, bindings, docs, and products built on the same runtime.
Loom (Apache 2.0)
M-POLY-VTD engine: train + infer, 21 dtypes, WebGPU, BitNet CPU, C-ABI welvet, native release binaries.
Polyglot bindings
Python, TypeScript/npm, Go, Dart, C#, Java, WASM—one engine, same weights, embed like SQLite for neural nets.
SoulGlitch (product)
Offline AI companion on Google Play—swarm Q&A, emotion training, reactive face. Living proof of on-device Loom.
Primecraft + lab tools
Voxel simulation with embedded AI, scene gallery, Lucy CLI for local HF models—same sovereignty story.
Open source means Loom: source, license, and rebuildable natives on GitHub.
Releases ship prebuilt .so / .dylib / wheels so you don't have to compile Go—same pattern as PyTorch pip wheels or llama.cpp binaries.
SoulGlitch is a product on Google Play (app code not necessarily OSS). Model weights come from Hugging Face under their own licenses.
What Loom does differently
Compared to cloud AI, Python frameworks, LLM-only runners, and other Go ML libraries.
Sovereign & offline
No API keys. Prompts and training stay on your hardware—privacy by architecture, not policy PDFs.
Pure Go, zero CGO
Golang AI without a Python runtime or CUDA-only trap. Single-binary deployment story for edge and servers.
3D volumetric mesh
Networks as spatial grids—not only nn.Sequential. Native target propagation and step mesh learning.
21 dtypes + BitNet
Float64 down to 1-bit binary per layer. Native packed checkpoints. BitNet b1.58 on CPU in v0.78.
DNVM determinism
Bit-identical behaviour across CPU, WebGPU, and bindings—reproducible research and embedded systems.
WebGPU everywhere
Cross-vendor GPU: Windows, Linux, macOS, Android, browser—without shipping CUDA toolchains per platform.
DNA & NEAT built-in
Topological comparison of whole networks, evolution in-engine—not just weight checkpoint diffing.
Shipped proof
SoulGlitch on Play Store today. Not slides—a consumer app running local LLMs via Loom/welvet.
Quick comparisons
Cloud AI (ChatGPT, etc.)
- Them: Intelligence in their datacenter
- Loom: Engine in your process
- Them: No embeddable runtime
- Loom: C-ABI for your app
PyTorch / JAX
- Them: Python + huge CUDA stack
- Loom: Go binary, edge-first
- Them: 1D autograd DAG
- Loom: 3D mesh + target propagation
llama.cpp / Ollama
- Them: LLM inference focus
- Loom: Train + small nets + NEAT + DNA
- Them: GGUF decode excellence
- Loom: Full engine for products
GoMLX / Born ML
- Them: 1D stacks or OpenXLA/CGO
- Loom: Zero CGO + WebGPU
- Them: Narrower scope
- Loom: DNVM, BitNet, DNA, shipped app
Loom vs PyTorch & Go ML (summary)
| Capability | Loom | PyTorch / JAX | llama.cpp |
|---|---|---|---|
| Core language | Pure Go (golang AI) | Python + C++/CUDA | C/C++ |
| Offline / embed | First-class (C-ABI, WASM) | Possible, heavy | Inference-focused |
| Training + custom nets | 3D mesh, NEAT, DNA | Autograd ecosystem | Mostly inference |
| Quantization | 21 native dtypes + BitNet CPU | TorchAO add-ons | GGUF quants |
| GPU path | WebGPU (cross-platform) | CUDA / ROCm / TPU | CPU/GPU backends |
| Determinism (DNVM) | Bit-exact claim | Not guaranteed | Varies |
| Open source | Apache 2.0 engine + binaries | Framework OSS | OSS inference |
Deep dive: M-POLY-VTD architecture research · docs overview
When to choose Loom
Choose Loom if you need…
- Offline AI inside your app (Flutter, Go, WASM)
- A golang AI / Go ML stack without Python
- Bit-exact, auditable local inference
- BitNet or sub-byte models on CPU
- 3D / NEAT / DNA research in one engine
- Apache 2.0 you can fork and ship
Use something else if you need…
- Largest cloud models with zero setup (use hosted APIs)
- Massive PyTorch ecosystem & HF fine-tune recipes day one
- Fastest GGUF Llama on Mac CPU only (benchmark llama.cpp)
- Enterprise MLOps (Kubeflow, etc.) out of the box
Ready to try the golang AI engine?
Star the repo, read the docs, or install SoulGlitch and run models offline today.