NeMo Data Designer vs Synthia

NeMo Data Designer is a compound AI system for generating synthetic data. Users configure dataset columns and models, preview sample records, then create a dataset. Its framework manages batching and parallelism, checks generated data, and supports statistical diversity, field correlations, and reproducible workflows. It handles tabular data, text, code, structured JSON, images, and embeddings, with CSV, JSON, JSONL, and Parquet output formats. The system is available as an open-source Python library or as a NeMo Microservice with REST API methods for previewing and creating datasets. Documented LLM endpoints include NVIDIA API Catalog, OpenAI, Azure OpenAI, Anthropic, vLLM, TGI, TensorRT-LLM, and OpenAI-compatible servers. The microservice also connects with NeMo Inference Microservices, NeMo Customizer, and NeMo Evaluator. Data Designer does not host models, so users need to supply LLM endpoints and inference capacity. The hosted free trial requires an API key; jobs default to 10 records and allow up to 100 per job. The default SECURE Jinja renderer includes sandboxing and output safeguards.

Synthia has no write-up on Specifiction yet; its figures are above.