Distillfast vs Building Fine-Tuning In-House
Building fine-tuning infrastructure in-house takes 3–6 months and costs ₹30–60 lakh in engineering time. Distillfast does it in 30 minutes for a fraction of the cost.
Feature
Building In House
Distillfast
Time to first model
3–6 months
< 1 hour
Engineering cost
₹30–60L (2 ML engineers, 3 months)
₹2,499/month
GPU infrastructure
Self-managed (AWS/RunPod)
Managed, included in plan
Synthetic data pipeline
Build from scratch
Included
Eval / regression guard
Build from scratch
DistillScore + auto-promotion
Auto-retrain scheduler
Build from scratch
Included, configurable
Ongoing maintenance
High — GPU, infra, updates
Zero — fully managed
Model portability
You own everything
You own weights, downloadable
Custom training logic
Full flexibility
Standard QLoRA (covers 95% of cases)
Our verdict
Building in-house makes sense if you have unique training requirements that no SaaS can meet. For the other 95% of use cases — support AI, document processing, classification — Distillfast is faster, cheaper, and ready now.
Try Distillfast free
2 models included. No credit card. Fine-tune in under an hour.
More comparisons: