karpathy/autoresearch

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

94753 stars · 13361 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A framework by Andrej Karpathy where AI agents autonomously run LLM research experiments on a single-GPU nanochat training setup. The agent edits train.py, trains for a fixed 5-minute budget, evaluates val_bpb, and iterates overnight based on program.md instructions.

Use cases

• run autonomous AI agent experiments on LLM training
• let an AI agent improve a GPT training loop overnight
• automate machine learning research experiments on a single GPU
• experiment with agent-driven code modification and evaluation loops
• set up an autonomous AI research organization with program.md
• benchmark architecture and optimizer changes fairly with val_bpb

When to choose

• you have a single NVIDIA GPU and want to explore autonomous AI-driven ML research
• you want a minimal, hackable baseline for agent-run training experiments
• you want to learn how LLM training works and watch agents iterate on it

When to avoid

• you need production LLM training at scale or multi-node clusters
• you have no NVIDIA GPU available
• you need a stable, licensed dependency for production systems (no license is provided)

Facets

framework · maturity active

agent-framework llm-training machine-learning prompt-engineering artificial-intelligence large-language-models machine-learning deep-learning python cli autonomous-research nanochat single-gpu ai-agents experiment-automation self-improving-code karpathy gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="karpathy/autoresearch")