vLLM
Inference engine for large language models built around PagedAttention, which pages the attention cache to raise batch sizes and throughput. Exposes an OpenAI-compatible API.
Optimized AI inference designed for production workloads that demand speed and efficiency. vLLM provides state-of-the-art inference optimization with features like continuous batching and PagedAttention, dramatically improving throughput for language models. This combo addresses the performance gap between development and production AI serving - while Ollama is perfect for experimentation, vLLM is engineered for scenarios where you need to serve many concurrent users with minimal latency. The setup includes OpenAI-compatible APIs, making it easy to switch existing applications from development to production serving without code changes.
Inference engine for large language models built around PagedAttention, which pages the attention cache to raise batch sizes and throughput. Exposes an OpenAI-compatible API.
Gateway fronting more than 100 model providers behind a single OpenAI-compatible API, adding routing rules, fallback chains, retries, per-key spend limits and request logging.