Alibaba PAI released SearchQwen2.5-7B, an open-weight search agent model
Model: Qwen2.5-7B-Instruct · availability, license and releases
Alibaba Cloud PAI released SearchQwen2.5-7B, a 7.62B-parameter search agent model based on Qwen2.5-7B-Instruct, on Hugging Face under Apache-2.0. It is trained with EasyDistill 2.0 and SynSearch-Data, and supports structured search/browse tool calls.
China context
- Original name
- SearchQwen2.5-7B
- Outside China
- Open weights · huggingface.co
- Claims
- Company-reported; not yet independently evaluated
- For builders
- Developers outside China can download the weights from Hugging Face and integrate the model into their own search pipelines, using the structured tool-call interface with any search/browse backend.
- For investors
- The release of an open-weight search agent model by Alibaba PAI may pressure commercial search API providers to differentiate on quality or price, as enterprises gain a self-hostable alternative.
Translated from Chinese. Quotes and facts link to the original sources.
Alibaba Cloud PAI released SearchQwen2.5-7B, a compact search agent model based on Qwen2.5-7B-Instruct, on Hugging Face under Apache-2.0. The model is trained with environment-aligned, solver-verified search trajectories generated by EasyDistill 2.0, and is designed for multi-hop search, browsing, and evidence integration. It supports structured search/browse tool calls and requires an external search/browse backend.
The model is a 7.62B-parameter transformer with a context length of 32,768 tokens, fine-tuned from Qwen/Qwen2.5-7B-Instruct. It uses a structured tool-call interface where the model returns a tool call, the tool is executed, and the response is appended until a final answer is produced. Reported LLM-judge accuracy: Multi-hop QA 55.90% (vs 45.23% for base), Deep Search 33.33% (vs 24.35%), Overall 44.61% (vs 33.33%).
Developers outside China can now use an open-weight search agent model under Apache-2.0, reducing the cost and complexity of building multi-hop search and browsing applications compared to proprietary APIs. Competitors offering search-augmented models must match this capability or risk losing developer mindshare.
The model enables enterprises to deploy search agent capabilities on-premises or in private clouds without per-query API costs, potentially lowering total cost of ownership for search-intensive applications. The Apache-2.0 license permits commercial use and modification.
Next signals to check: whether Alibaba PAI releases larger SearchQwen variants, whether the SynSearch-Data training set is made public, and whether third-party evaluations confirm the reported accuracy gains on multi-hop QA and deep search benchmarks.