Qwen2.5-1M: Deploy Your Own Qwen with Context Length up to 1M Tokens
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Qwen Team
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Qwen Team
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Terms in this piece · Glossary
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
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.
open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
Why it matters
Qwen2.5-1M lets you run open weightsA model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.Full definition → 7B/14B instruct models with up to 1M-tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition →context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → locally, with an included inferenceRunning a trained model to get answers — the phase where AI is actually used, as opposed to trained.Full definition → framework tuned for long-context throughput — useful when you need to reason over entire codebases or large document sets without relying on a closed API.