📖 The AI Tool Bible

LLaMA Factory vs Modal

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
LLaMA Factory
Fine-tuning
Modal
Fine-tuning
TaglineOpen-source, no-code WebUI for fine-tuning 100+ open LLMs with LoRA, QLoRA, DPO, and PPO.Serverless GPUs and infra for training & serving ML.
CategoryFine-tuningFine-tuning
PricingFree· Free, open-source (Apache-2.0); self-hostedFreemium· $30/mo free credits; pay-as-you-go GPU rates
ModelMulti-model (LLaMA, Mistral, Qwen, Gemma, Phi, LLaVA, ChatGLM, Yi)Infrastructure (any model you can host)
Editorial score—8.7 / 10
Use cases
lora-fine-tuningqloradpo-alignmentinstruction-tuningrlhfvlm-fine-tuning
serverless GPUfine-tuningbatch inference
Pros
  • No-code WebUI (LlamaBoard) covers SFT, DPO, PPO, KTO, and reward modeling
  • Supports 100+ open models including multimodal VLMs out of the box
  • Full QLoRA stack (2-8 bit) plus LoRA+, DoRA, PiSSA variants
  • Acceleration via FlashAttention-2, Unsloth, Liger Kernel, vLLM inference
  • Exports to GGUF / Ollama and integrates with W&B, MLflow, TensorBoard
  • Zero-ops GPU access
  • Python-native
  • Auto-scaling
  • Honest pay-per-second pricing
Cons
  • Self-hosted only — you bring the GPUs and the ops
  • Rapid release cadence means version pinning is essential
  • WebUI abstracts but does not solve VRAM and dataset-formatting pitfalls
  • Cold start latency on big models
  • Bills can surprise at scale
Websitellamafactory.readthedocs.iomodal.com
Pick LLaMA Factory if
  • ✅ No-code WebUI (LlamaBoard) covers SFT, DPO, PPO, KTO, and reward modeling
  • ✅ Supports 100+ open models including multimodal VLMs out of the box
  • ✅ Full QLoRA stack (2-8 bit) plus LoRA+, DoRA, PiSSA variants
  • ✅ Acceleration via FlashAttention-2, Unsloth, Liger Kernel, vLLM inference
Pick Modal if
  • ✅ Zero-ops GPU access
  • ✅ Python-native
  • ✅ Auto-scaling
  • ✅ Honest pay-per-second pricing
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