Scale GenAI Platform vs Together AI

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

	Scale GenAI Platform Fine-tuning	Together AI Fine-tuning
Tagline	Enterprise agent platform from Scale AI that connects your data, orchestrates multi-agent workflows, and learns from human feedback inside your own VPC.	Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).
Category	Fine-tuning	Fine-tuning
Pricing	Enterprise· Contact sales; enterprise contracts only	Paid· Pay-per-token; fine-tuning per-token
Model	Multi-model (OpenAI, Google, Meta, Mistral)	Llama / Mistral / Qwen / DeepSeek and others
Editorial score	—	8.6 / 10
Use cases	enterprise-agentsrag-over-internal-datamulti-agent-workflowshuman-feedback-loopsregulated-industries	open modelsfine-tuninginference
Pros	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	Wide open-model catalogue Competitive inference pricing Fine-tune + serve in one place Dedicated endpoints for production
Cons	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	Latency varies by model Less polish than OpenAI
Website	scale.com	www.together.ai

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

Pick Together AI if