Documentation
README
slime: LLM Post-Training Framework for RL Scaling
slime is an LLM post-training framework from Tsinghua's THUDM team, powering GLM-4.5, GLM-4.6, and GLM-4.7. It connects Megatron-LM for training with SGLang for high-throughput rollout generation.
When to Use slime
Choose slime when you need:
- Megatron-LM native training with SGLang inference
- Custom data generation workflows with flexible data buffers
- Training GLM, Qwen3, DeepSeek V3, or Llama 3 models
- Research-grade framework with production backing (Z.ai)
Consider alternatives when:
- You need enterprise-grade stability features → use miles
- You want flexible backend swapping → use verl
- You need PyTorch-native abstractions → use torchforge
This is the opening of the README. Read the full README on GitHub.