“OpenRouter, Ollama, as you mentioned, they're all great partners and friends in the ecosystem because we're there to understand how everybody else can leverage AI model better.”
Source→“Ollama makes it easy to run large language models locally—on a developer laptop, a workstation, or on-prem servers—without sending prompts and data to a hosted API... $65M raise”
“That's becoming a default requirement in regulated environments and inside enterprises that want AI features but can't accept data leakage, latency, or unpredictable inference costs.”
“Ollama, MLX, and WASTE — which to use when, with the commands and the quantization cheat sheet”
Source→“Ollama, MLX, and WASTE — which to use when, with the commands and the quantization cheat sheet.”
Source→“Raises $65M Series B Round from GTMfund, 8VC, Theory Ventures, Y Combinator, Benchmark”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.