Soup 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 Soup among their alternatives. The relationship is not symmetric — how Soup rates them is a separate judgement, made when Soup is analysed in its own right.
calls Soup “Choose for very low-memory fine-tuning via layer streaming when your GPU is smaller than Unsloth's typical requirement.”
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 Soup “choose when you need memory-efficient layer streaming to train larger models on severely limited GPUs.”
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
calls Soup “Choose when you must fine-tune on a very low-VRAM laptop GPU using layer streaming, accepting much narrower model/algorithm coverage.”
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 Soup “Choose it for YAML-driven fine-tuning that fits an 8B model on a 4 GB laptop GPU, accepting much narrower scope than Oumi.”
Easily fine-tune, evaluate and deploy Qwen, Gemma, or any open weight LLM!