Qwen2.5-1M-7|14B

Overview

Qwen2.5-1M-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M are open-source language models upgraded to handle up to 1 million tokens of context. They are accompanied by an inference framework designed to support this extended context length. The models are released as checkpoints and are available on HuggingFace and ModelScope.

Best for

Best for
Developers who need open-source models with very long context capabilities for document processing or code analysis

Use cases

• Analyzing and summarizing very long documents or books
• Processing large codebases for refactoring or debugging
• Handling extended multi-turn conversations with full history

Notes

Qwen2.5-1M-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M are open-source language models upgraded to handle up to 1 million tokens of context. They are accompanied by an inference framework designed to support this extended context length. The models are released as checkpoints and are available on HuggingFace and ModelScope.

Use cases

• Analyzing and summarizing very long documents or books
• Processing large codebases for refactoring or debugging
• Handling extended multi-turn conversations with full history

Pros

• Supports up to 1M tokens of context, surpassing many alternatives
• Open-source with community-accessible checkpoints
• Includes dedicated inference framework for efficient long-context usage

Cons

• Large models (7B and 14B) require significant GPU memory for inference
• Long context may lead to slower inference times compared to shorter models
• Relatively new with limited third-party tooling and optimization

Indexed from awesome-llm and enriched against its public facts.