Codersarts Blog.

Introduction You've finally convinced your team to self-host an LLM. You've chosen a 7B parameter model, spun up a cloud instance with two A100s, and written a basic Python script to load the model and generate text. Then reality hits: your inference server processes one request at a time, leaving 90% of your GPU compute idle. Concurrent users wait in line. Memory overflows mid-generation. And worst of all, migrating your existing OpenAI client code to hit your new server req