trevin-creator/autoresearch-mlx

Health v2 · maintenance only

Flags: no_releases young

Adoption not part of the score

1813 stars · 364 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

An Apple Silicon (MLX) port of Karpathy's autoresearch that runs autonomous AI research loops on a Mac without PyTorch or CUDA. A coding agent iteratively edits a single train.py, runs fixed 5-minute training experiments, and keeps or reverts changes based on validation bits-per-byte.

Use cases

• run autonomous ML training experiments on Apple Silicon
• let a coding agent optimize a training loop automatically
• do LLM training research on a Mac without CUDA
• benchmark model configs under a fixed time budget
• explore hyperparameter search with keep-or-revert git workflow
• port PyTorch research loops to MLX

When to choose

• you have an Apple Silicon Mac and no NVIDIA GPU
• you want agent-driven autonomous experimentation with MLX
• you want a minimal, transparent research loop controlled by a markdown protocol

When to avoid

• you need PyTorch or CUDA ecosystem compatibility
• you need large-scale multi-GPU training
• you want a turnkey training pipeline rather than an experimental loop

Facets

framework · maturity active

llm-training machine-learning benchmarking developer-tools machine-learning deep-learning artificial-intelligence developer-tools python mlx apple-silicon autonomous-research agent-driven-experiments neural-network-training hyperparameter-search karpathy-port macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="trevin-creator/autoresearch-mlx")