xtuner is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
These projects were analysed and named xtuner among their alternatives. The relationship is not symmetric — how xtuner rates them is a separate judgement, made when xtuner is analysed in its own right.
calls xtuner “Choose for a specialized engine aimed at training very large MoE models, not a consumer GUI.”
Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.
calls xtuner “Choose when you want a training engine specialized for ultra-large MoE/InternLM-scale models and plan to deploy through the LMDeploy ecosystem.”
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.6, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Gemma4, Llava, Phi4, ...) (AAAI 2025).
calls xtuner “Choose it for ultra-large MoE training at scale on GPU clusters, as a specialized throughput engine rather than a general end-to-end platform.”
Easily fine-tune, evaluate and deploy Qwen, Gemma, or any open weight LLM!