Qwen 3 32B Instruct, Yi 1.5 34B Chat, and Yi 1.5 9B Chat all come from Chinese AI labs — Alibaba's Qwen team and 01.AI respectively — and all target bilingual English/Chinese production use. The models are separated by about a year in release date and a substantial generation in architecture: the Yi 1.5 series launched May 2024, while Qwen 3 arrived in 2025 with a redesigned instruction-tuning pipeline and a dramatically extended context window. Yi 1.5 9B Chat offers solid English and Chinese performance for its 9B scale. MMLU sits around 69.5, competitive at release in mid-2024. The 4K context ceiling is the hard constraint: it disqualifies the model for most RAG pipelines and any document-length task. Apache 2.0 licensing makes it a clean fine-tuning base for bilingual workloads where those context limits are acceptable. Yi 1.5 34B Chat scales to 34B parameters and delivers competitive MT-Bench and CMMLU scores. The 4K context ceiling is identical to the 9B variant, disqualifying it for modern RAG pipelines. By mid-2025, Qwen 2.5 and DeepSeek V2 in the same size class moved ahead on both context and benchmark numbers. Yi 1.5 34B is relevant mainly where Apache 2.0 licensing and specific bilingual pretraining distributions are both required. Qwen 3 32B Instruct is the current-generation comparison point. At 32B parameters with 131K context and the Qwen 3 multilingual instruction-tuning improvements, it outperforms both Yi models on general benchmarks and handles document-length tasks neither Yi model can attempt. The Qwen license permits commercial use. The trade-off is that Qwen 3 is not Apache 2.0, so teams with strict OSI-license requirements may still favor Yi 1.5. Pick Yi 1.5 9B for low-scale bilingual tasks with an Apache 2.0 requirement. Pick Yi 1.5 34B when Apache 2.0 and 34B-class quality are both needed within a 4K context budget. Pick Qwen 3 32B for any workload that needs modern long-context handling or current-generation benchmark quality.