OpenAI Fine-tuning vs Scale GenAI Platform

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

	OpenAI Fine-tuning Fine-tuning	Scale GenAI Platform Fine-tuning
Tagline	Fine-tune GPT-4o-mini and friends on your own data.	Enterprise agent platform from Scale AI that connects your data, orchestrates multi-agent workflows, and learns from human feedback inside your own VPC.
Category	Fine-tuning	Fine-tuning
Pricing	Paid· Basic: $10 · Pro: $25 · Enterprise: Contact sales	Enterprise· Contact sales; enterprise contracts only
Model	GPT-4o-mini / GPT-3.5	Multi-model (OpenAI, Google, Meta, Mistral)
Editorial score	8.4 / 10	7.1 / 10
Use cases	styleformatdomain knowledge	enterprise-agentsrag-over-internal-datamulti-agent-workflowshuman-feedback-loopsregulated-industries
Pros	Easiest fine-tuning UX Vision FT now supported Works inside the OpenAI ecosystem Same infra/SLA as base models	Deploys inside your own VPC on AWS, Azure, or GCP so data never leaves Model-agnostic, avoiding lock-in to a single LLM vendor Built-in evaluation, monitoring, and human-feedback loop for continuous improvement Backed by Scale's mature data-labeling and RLHF operation Open-source components (Agentex, AgentOps) let you prototype before buying
Cons	Pricier than open-model FT No weights export	No public pricing; enterprise sales cycle only Overkill and too expensive for small teams or solo builders Heavy implementation effort versus plug-and-play agent SaaS
Website	platform.openai.com	scale.com

Pick OpenAI Fine-tuning if

Pick Scale GenAI Platform if

✅ Deploys inside your own VPC on AWS, Azure, or GCP so data never leaves
✅ Model-agnostic, avoiding lock-in to a single LLM vendor
✅ Built-in evaluation, monitoring, and human-feedback loop for continuous improvement
✅ Backed by Scale's mature data-labeling and RLHF operation