Tencent’s Hy4 model gains in open-source AI rankings after ecosystem-driven training
Tencent’s new Hy4 preview model has achieved an eighth-place global ranking on Code Arena’s WebDev leaderboard, surpassing Alibaba’s Qwen 3.8-Flash-Next. This marks a significant improvement from its predecessor, Hy3, which ranked 34th. The Hy4 preview also scored 64.3 on the DeepSWE benchmark, outperforming Alibaba’s Qwen-3.8 Max at 56.6 and DeepSeek-V4 Pro at 62.7. Analysts attribute these gains to Tencent’s strategy of training its models using data from its extensive product ecosystem.
Tencent’s Hy4 preview model demonstrates how a closed-loop product-plus-model strategy can drive AI agent development. By deploying preview models across its product suite, Tencent collects user data to refine subsequent training rounds. This approach is particularly effective for coding and productivity workloads, where real-world interactions improve model differentiation. This strategy has propelled Tencent’s Hunyuan series back into the top tier of open-source models, with notable improvements in coding capabilities over Hy3. For China’s tech sector, this suggests a competitive edge in AI development, as companies with vast user ecosystems can leverage internal data for rapid model iteration and performance gains. The key watch point is how quickly other Chinese tech giants can replicate or counter this ecosystem-driven training model.
分享这篇文章
相关文章
6 则
Frontier AI at a cost: what Anthropic’s Fable 5.1 means for the US-China model race
The US-China model race is heating up, and Tencent's strategy offers a unique competitive edge.

美国还是中国?哈萨克斯坦在人工智能革命中拒绝选边站队

LUXEED 与 Aimoga 机器人:通过互联的人车家生态系统共同构建未来出行

马来西亚希望摆脱Waze。司机们会转用吗?

Stripe 发票不等于收入:如何通过网络钩子将其转化为 ASC 606 附表

