关于Qwen3 GGUF版本中IMatrix使用效果的探讨
感谢你们开源了优秀的Qwen3系列模型！这些模型性能出色，让普通用户也能直接在本地运行。
我注意到在发布的GGUF版本中，根据元数据显示没有使用imatrix。能否请您谈谈在Qwen3系列上创建GGUF时使用imatrix的价值？或者你们发现对于4bpw及以上位宽的量化而言这是不必要的？
之所以询问这个问题，是因为在Reddit的r/LocalLLaMA等论坛上有相关讨论，比较类似尺寸GGUF模型的相对性能，包括标准imatrix以及针 特定模型token和更长上下文长度优化的专用imatrix方案。
由于全面测试所有量化版本可能比较困难，或许你们团队已经掌握了一些相关数据。感谢分享！祝好！
Question Regarding IMatrix in Qwen3 GGUF Releases
Thanks for releasing the great Qwen3 series in open weights! These models offer great performance for the common person to run directly at home.
I noticed with your GGUF release, there is no imatrix used according to the metadata. Could you speak to the value of imatrix during GGUF creation on the Qwen3 series, or do you find it is not necessary for 4bpw or higher quants?
I ask because there are discussions on forums like reddit's r/LocalLLaMA discussion relative performance of similar sized GGUFs including standard imatrix as well as specialized imatrix with model specific tokens and longer context lengths.
It can be difficult to benchmark all of the quants, so maybe your team has some knowledge already. Thanks for sharing! Cheers!