Companies Building the Best Businesses on Open AI Models

Together turns open models into managed training and inference infrastructure. Companies get flexibility without assembling every GPU, driver and serving layer themselves.

Fireworks makes open-model inference fast and comparatively easy to measure. Lower latency and cost are clearer sales arguments than vague claims about intelligence.

Databricks can place open models beside the proprietary data its customers already manage. That proximity makes customization and governance more practical.

Alibaba’s Qwen family gives its cloud a widely used developer ecosystem beyond China. Open releases create adoption that ordinary enterprise sales cannot buy.

Open models give Groq’s specialized inference hardware an immediate catalog of useful workloads. Users can feel the speed without adopting a proprietary model.

Hugging Face became the default place to publish, discover and test open models. Its community and tooling give the company a position beyond hosting files.

Mistral pairs strong open-weight models with paid enterprise products and a European sovereignty argument. Customers can buy support without surrendering deployment control.

Thomson Reuters trained a specialist model on Qwen for professional research, reducing dependence on closed APIs while protecting valuable domain knowledge.

Cloudflare runs open models across its global network, moving inference nearer to users and turning existing infrastructure into an accessible AI platform.

IBM can combine open models with Red Hat software and long enterprise relationships. The pitch suits customers that care more about control than novelty.