oMLX
LLM inference server with continuous batching & SSD caching
...It serves text models, vision-language models, OCR models, embeddings, and rerankers through OpenAI- and Anthropic-compatible APIs. Continuous batching allows concurrent requests, while a tiered KV cache keeps active data in RAM and moves colder blocks to SSD for reuse. Models can be pinned, unloaded manually, or evicted automatically when memory runs low. A web dashboard provides monitoring, chat, downloads, benchmarks, integrations, and per-model settings. It also supports tool calling, structured output, MCP integration, and experimental multi-Mac inference.