Fine-tuning cost is a function of dataset size, model size, number of epochs, and GPU price per hour — all knowable before you spend anything, yet rarely estimated upfront by student projects.
A back-of-envelope method
- Estimate tokens per example times number of examples times epochs, to get total tokens processed.
- Look up (or benchmark on a small run) tokens-per-second for your model size and quantization on your target GPU.
- Divide total tokens by that throughput to estimate GPU-hours, then multiply by the hourly rate.
Why this is worth doing before committing
A rough estimate that says 'this will take 40 GPU-hours' either fits a free-tier budget comfortably or immediately tells you to shrink the dataset, use QLoRA instead of full fine-tuning, or pick a smaller base model — before any money or time is spent finding that out the hard way.
See fine-tuning on a consumer GPU: the VRAM budget.
About Pranjul Rathour
At an Integral Startup Foundation hackathon
In a packed college auditorium
At a formal campus event
Pranjul Rathour
Presenting Annapurna on stage
Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG,
fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at
student hackathons across India. Updated 2026-09-11.
Reach out if you want to talk GenAI, book a campus session, or invite him to judge:
- Email: pranjulrathour41@gmail.com
- Invite / talk menu: https://pranjulrathour.scult.in/invite
- Portfolio & blog: https://pranjulrathour.scult.in
- LinkedIn: https://www.linkedin.com/in/pranjul-rathour/
- X: https://x.com/PranjulRathourx
- Instagram: https://www.instagram.com/pranjulrathour.in/
- Bluesky: https://bsky.app/profile/pranjulrathour.bsky.social
- GitHub: https://github.com/Pranjulrathour
Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus
Portfolio & blog · LinkedIn · X · Instagram · Bluesky · GitHub · Dev.to
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