Production-ready AI models for business. These 235 models support at least 3 enterprise capabilities — function calling, JSON mode, streaming, vision, and reasoning — making them suitable for deployment in real-world applications and automated workflows.
| Provider | Enterprise Models | Share |
|---|---|---|
| OpenAI | 54 | 23% |
| Alibaba | 47 | 20% |
| Mistral AI | 22 | 9% |
| 21 | 9% | |
| Anthropic | 13 | 6% |
| DeepSeek | 12 | 5% |
| Meta | 9 | 4% |
| NVIDIA | 8 | 3% |
| xAI | 8 | 3% |
| Moonshot AI | 5 | 2% |
| Amazon | 4 | 2% |
| MiniMax | 4 | 2% |
Enterprise workflows require models that can invoke external APIs, query databases, and interact with business systems through structured tool definitions. Function calling transforms an LLM from a text generator into an autonomous agent.
Production systems need machine-readable output. JSON mode guarantees structured responses that can be parsed reliably, eliminating the brittleness of free-form text parsing in automated pipelines.
Real-time applications demand incremental output. Streaming reduces perceived latency for end users and enables progress indicators in customer-facing products, a requirement for enterprise UX standards.
Multimodal input lets models process documents, charts, screenshots, and images. Enterprise use cases like document understanding, visual QA, and OCR workflows depend on robust vision capabilities.
Complex business decisions require chain-of-thought reasoning. Models with dedicated reasoning capabilities handle multi-step analysis, compliance checks, and strategic planning tasks more reliably.
We score enterprise readiness from 1 to 5 based on how many of the above capabilities a model supports. Models with 3 or more capabilities (shown on this page) are considered enterprise-ready. The composite score ranks overall model quality.