NovaSky-AI/SkyRL
SkyRL: A Modular Full-stack RL Library for LLMs observed · 2026-08-28
Health v2 · maintenance only
80/100
- Activity 99
- Release rhythm 81
- Longevity 35
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 52.0
- age_days: 498
- days_rel: 48
- days_push: 9
- n_releases_24m: 7
Adoption not part of the score
2201 stars · 410 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
SkyRL is a modular full-stack reinforcement learning library for post-training large language models, combining a training framework (skyrl-train), a Tinker API-compatible backend (skyrl-tx), an agent layer for long-horizon tasks (skyrl-agent), and a Gymnasium-style environment library (skyrl-gym). It supports FSDP and Megatron training backends with vLLM inference on your own NVIDIA GPUs, including LoRA and full-parameter fine-tuning.
Use cases
- train llm with reinforcement learning on my own gpus
- run tinker api training scripts locally without code changes
- fine-tune llm with grpo on gsm8k
- build custom gym environments for rlhf training
- train multi-turn tool-use agents with rl
- rl post-training for sql and search agents
- supervised fine-tuning of large language models with lora
- train vision-language models with reinforcement learning
When to choose
- you want to run RL post-training (GRPO, PPO, DAPO) for LLMs on your own NVIDIA hardware
- you need Tinker API compatibility with zero code changes on local GPUs
- you are training long-horizon, multi-turn tool-use agents
- you want a modular RL stack with pluggable environments, trainers, and inference engines
- you need to scale from 0.5B to 200B+ parameter models with FSDP or Megatron
When to avoid
- you only need simple SFT without RL and prefer lightweight fine-tuning tools
- you have no NVIDIA GPUs or CUDA 13.0-capable drivers
- you want a fully managed hosted training service rather than self-managed infrastructure
- you need RL for non-LLM domains like robotics control
Facets
library · maturity active
machine-learning llm-training agent-framework gpu-computing sdk large-language-models reinforcement-learning machine-learning gpu-computing python cloud reinforcement-learning rlhf grpo tinker-api fsdp megatron vllm ray lora post-training gymnasium-environments multi-turn-agents ai-agents gpu docker linux
10 sources
- readme: https://github.com/NovaSky-AI/SkyRL · fetched 2026-08-28 · a789e897cf5f
- homepage: https://docs.skyrl.ai/docs · fetched 2026-08-29 · 5f840523ae09
- site_page: https://docs.skyrl.ai/docs/tinker/architecture · fetched 2026-08-29 · 9c84a192532d
- site_page: https://docs.skyrl.ai/docs/tinker/cookbook · fetched 2026-08-29 · 609885930091
- site_page: https://docs.skyrl.ai/docs/tutorials/new_env · fetched 2026-08-29 · 226c5827a321
- site_page: https://docs.skyrl.ai/docs/tinker/overview · fetched 2026-08-29 · 6109706116f7
- site_page: https://docs.skyrl.ai/docs/getting-started/installation · fetched 2026-08-29 · 33b8ffed345c
- site_page: https://docs.skyrl.ai/docs/getting-started/quickstart · fetched 2026-08-29 · f2bd0cd5ac8d
- site_page: https://docs.skyrl.ai/docs/getting-started/overview · fetched 2026-08-29 · e8e0b7772ec3
- site_page: https://docs.skyrl.ai/docs/tinker/quickstart · fetched 2026-08-29 · 77452d3188d2
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| NovaSky-AI/SkyRL | main | 80 |
For agents
markdown · JSON · MCP: product_card(name="NovaSky-AI/SkyRL")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem