Qwen2.5-1M: Deploy Your Own Qwen with Context Length up to 1M Tokens
Qwen ● Covered by 3 sources
Alibaba released open-source Qwen2.5-1M models, including 7B and 14B parameter versions that support context lengths up to 1 million tokens. The inference framework achieves 3.2x to 6.7x faster processing speeds on 1M-token sequences compared to baseline approaches, with the 14B model matching GPT-4o-mini performance on short texts while supporting eight times longer context. Developers can now deploy these models locally using the open-sourced vLLM-based framework, which requires 120GB VRAM for the 7B model and 320GB for the 14B model.
Why it matters
Tech Report HuggingFace ModelScope Qwen Chat HuggingFace Demo ModelScope Demo DISCORD Introduction Two months after upgrading Qwen2.5-Turbo to support context length up to one million tokens, we are back with the open-source Qwen2.5-1M models and the corresponding inference framework support. Here’s what you can expect from this release: Opensource Models: We’re releasing two new checkpoints, Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, marking the first time we’ve upgraded our opensource Qwen models to handle 1M-token contexts.