📖 The AI Tool Bible

Modal vs Together AI Fine-tuning

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

 
Modal
Fine-tuning
Together AI Fine-tuning
Fine-tuning
TaglineServerless GPUs and infra for training & serving ML.Managed fine-tuning platform for open-source LLMs and vision models with LoRA, full fine-tuning, and RL support.
CategoryFine-tuningFine-tuning
PricingFreemium· $30/mo free credits; pay-as-you-go GPU ratesPaid· Usage-based; cost estimator in-product, no public price list
ModelInfrastructure (any model you can host)Multi-model (any Hugging Face open-source model)
Editorial score8.7 / 10—
Use cases
serverless GPUfine-tuningbatch inference
llm-fine-tuningvision-fine-tuningreinforcement-learningtool-calling-trainingdomain-adaptation
Pros
  • Zero-ops GPU access
  • Python-native
  • Auto-scaling
  • Honest pay-per-second pricing
  • Supports any open-source model on Hugging Face Hub
  • LoRA, full fine-tune, RL, and tool-calling in one platform
  • Vision fine-tuning on raw image data (Llama-4, Qwen3-VL)
  • SOC 2 Type II + ISO 27001 with regional data residency
  • Direct deploy to Together's inference stack after training
Cons
  • Cold start latency on big models
  • Bills can surprise at scale
  • No public pricing — cost estimator only after signup
  • Closed-source platform despite open-weight focus
  • Overkill for hobbyists who just want a quick LoRA
Websitemodal.comwww.together.ai
Pick Modal if
  • ✅ Zero-ops GPU access
  • ✅ Python-native
  • ✅ Auto-scaling
  • ✅ Honest pay-per-second pricing
Pick Together AI Fine-tuning if
  • ✅ Supports any open-source model on Hugging Face Hub
  • ✅ LoRA, full fine-tune, RL, and tool-calling in one platform
  • ✅ Vision fine-tuning on raw image data (Llama-4, Qwen3-VL)
  • ✅ SOC 2 Type II + ISO 27001 with regional data residency
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