Skip to content
SPECIFICTION
Get listed

NeMo Data Designer

build.nvidia.com

Free trial WebLinuxAPISelf-hosted
Visit build.nvidia.com
Spec score 7.8 #11 of 29 in Synthetic Data Generation Software

What it is

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.

Spec sheet

Purpose
NeMo Data Designer is a compound AI system for synthetic data generation.Read 5 Oct 2026 · build.nvidia.com
Audience
The open-source library is positioned for developers with LLM access who want flexibility and customization, while the microservice is for teams using NeMo Microservices.Read 5 Oct 2026 · docs.nvidia.com
Deployment
It is available as an open-source Python library and as a NeMo Microservice with REST API preview and create methods.Read 5 Oct 2026 · docs.nvidia.com
Integrations
Documented LLM endpoints include NVIDIA API Catalog, OpenAI, Azure OpenAI, Anthropic, vLLM, TGI, TensorRT-LLM, and OpenAI-compatible servers.Read 5 Oct 2026 · docs.nvidia.com
Security
The SECURE Jinja renderer is the default and adds a hardened sandbox, JSON-compatible context sanitization, template restrictions, and output guards.Read 5 Oct 2026 · docs.nvidia.com
Headquarters
Santa Clara, California, USARead 28 Sep 2026 · build.nvidia.com
Founded
1993Read 28 Sep 2026 · build.nvidia.com
Generation
The framework handles batching, parallelism, validation, statistical diversity, field correlations, and reproducible workflows.Read 5 Oct 2026 · docs.nvidia.com
Hosted trial limit
The hosted product page says jobs default to 10 records and allow up to 100 records per job.Read 5 Oct 2026 · build.nvidia.com
Hosting requirement
Data Designer does not host models; users must provide LLM endpoints and provision inference capacity.Read 5 Oct 2026 · docs.nvidia.com
NeMo integrations
The microservice integrates with NeMo Inference Microservices, NeMo Customizer, and NeMo Evaluator.Read 5 Oct 2026 · docs.nvidia.com
Output
The hosted walkthrough shows preview results available as a Pandas DataFrame.Read 5 Oct 2026 · build.nvidia.com
Workflow
Users configure columns and models, preview samples, then create a dataset.Read 5 Oct 2026 · docs.nvidia.com

Plans and prices

NeMo Data Designer free trial Free API key required · up to 100 records per job Read 5 Oct 2026 · build.nvidia.com

Every NeMo Data Designer plan and price →

Strong points and limits

Strong points

  • Open-source Python library and NeMo Microservice options
  • Supports six listed data modalities
  • Exports CSV, JSON, JSONL, and Parquet
  • Preview and create methods are available through REST API

Limits

  • Users must provide LLM endpoints and inference capacity
  • Hosted trial requires an API key
  • Hosted jobs allow up to 100 records each

Who it suits

The open-source library suits developers who have LLM access and want flexibility to customize synthetic data generation. Teams already using NeMo Microservices may prefer the microservice deployment.

Verdict

NeMo Data Designer offers flexible synthetic data workflows, multiple deployment options, and a range of input modalities and output formats. It depends on users supplying model access and inference capacity.

Where Specifiction places it

Alternatives to NeMo Data DesignerAll alternatives →