OpenAI turns general-purpose models into tools for work and applications
An OpenAI blueprint covering ChatGPT, Codex, the Responses and Agents APIs, current model pricing and a practical document-intake workflow.
The labs and the platforms the rest run on. Independent research in this category, newest first.
An OpenAI blueprint covering ChatGPT, Codex, the Responses and Agents APIs, current model pricing and a practical document-intake workflow.
Anthropic’s Claude spans user applications, coding workflows and a developer platform. Choosing the right product and model route matters as much as choosing the model.
Cerebras builds AI systems and serves models through cloud and dedicated routes. Its practical value depends on how much model generation contributes to the user’s wait.
DeepSeek offers developer model APIs with thinking, tool calling and caching. A dependable integration needs the current model names, response rules and billing windows.
Fireworks combines shared model inference, dedicated GPU deployments and fine-tuning. Choosing it means evaluating the adapted model and the system that will serve it.
The Hugging Face Hub hosts models, datasets and applications, with several routes to inference. A good choice starts with the artifact, license and operating model.
Together AI offers shared model APIs, dedicated deployments and training infrastructure. The useful choice is which serving route fits the workload and its data.
How Cohere’s Embed, Rerank, Command and North offerings fit together, with a worked knowledge-search architecture and a guide to deployment costs.
A practical guide to GroqCloud models, token pricing, tool calling and the tests that reveal whether faster inference improves your product.
A guide to Mistral’s model portfolio, Studio and document-processing APIs, including current usage prices and a worked extraction architecture.
How Replicate predictions, deployments and model pricing fit a real application, including asynchronous jobs, output retention and approved-asset costs.