context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
chunking — Splitting documents into passages small enough to embed and retrieve individually — the step that quietly determines whether retrieval works at all.
RAG — Retrieval-augmented generation — fetching relevant documents first and pasting them into the model's context so it answers from your data instead of memory.
Why it matters
Qwen2.5-Turbo pushes usable context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → to ~1M tokens (roughly a million English words), enabling whole-codebase or multi-document reasoning in a single call without chunkingSplitting documents into passages small enough to embed and retrieve individually — the step that quietly determines whether retrieval works at all.Full definition → or RAGRetrieval-augmented generation — fetching relevant documents first and pasting them into the model's context so it answers from your data instead of memory.Full definition → workarounds, plus reported inferenceRunning a trained model to get answers — the phase where AI is actually used, as opposed to trained.Full definition →-speed optimizations that make long-context practical rather than prohibitively slow.