Architecture comparison

AI21 Labs vs OpenAI

AI21 Labs runs closer to the foundational model (Native (own / self-hosted weights)) than OpenAI (Native (own / self-hosted weights)). No shared foundational model — different bets.

AI21 Labs

AI/LLM

Proximity

Native (own / self-hosted weights)

Models

proprietary / self-built models

Cloud · datastore

Multi-Cloud

Compliance

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Architecture

AI21 Labs develops and serves its own Jamba family of LLMs and related services via its AI21 Studio API and private deployments, while also distributing Jamba models through third‑party clouds such as Azure and upcoming NVIDIA APIs.[5][6][7] Public materials describe deployment options across public cloud and private/on‑prem environments but do not reveal a full production stack beyond this high‑level multi‑cloud posture.[3][5][6]

OpenAI

AI/LLM

Proximity

Native (own / self-hosted weights)

Models

OpenAI · GPT

Cloud · datastore

HybridAzure Cosmos DBPostgreSQLBlob/Object Storage (e.g., Azure Blob)Kafka (for event/log streaming)

Compliance

SOC 2 (inferred from enterprise-grade cloud use on Azure)[15][16]ISO 27001 (inferred from Azure AI and hyperscaler environments)[15][16]Regional data residency and enterprise controls via Azure/OpenAI Deployment Company (inferred)[15][19][20]

Architecture

OpenAI runs large GPU superclusters and Kubernetes-based orchestration across Azure and its own data centers in a hybrid setup, with Azure as the primary cloud and custom HPC clusters (e.g., Stargate) for training and serving frontier models.[15][16][19] Core application and API workloads use relational stores like PostgreSQL for accounts/settings and globally scalable databases such as Azure Cosmos DB plus Kafka streams for high-volume conversation, analytics, and event data.[1][8][12]

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