Tencent's Apache-Licensed Hy3 Model Takes on GLM-5.2 at Half the Size

For the past year, the awkward secret of the open-weight model boom has been that many of the strongest Chinese releases were off-limits to a large slice of the enterprises most interested in them. License terms that excluded the European Union, the United Kingdom and South Korea meant legal teams killed deployments before engineering teams finished their evals — not just for companies headquartered there, but for any enterprise serving traffic into those regions. Tencent just removed that obstacle.

The company's Hunyuan team released the full version of Hy3, a 295-billion-parameter Mixture-of-Experts (MoE) model with 21 billion active parameters, and — in a reversal from April's preview release — shipped it under the permissive Apache 2.0 license. The reaction from the open-model community was immediate, with researchers on X singling out the license change as the real headline, and one widely shared post arguing that if the scores hold up, Tencent has just become one of the leaders of open source. Tencent says it will be free on OpenRouter for two weeks.

The scores are worth scrutinizing — and they don't all point the same direction. But the more interesting story is what Tencent chose to lead with: reliability metrics and deployment economics aimed squarely at production use. From preview to product in ten weeks, shaped by 50 internal teams Hy3's April preview was the first model of Tencent's rebuilt pre-training and reinforcement learning infrastructure, shipped less than three months after the February rebuild.

Chief AI Scientist Shunyu Yao framed the early open release as a deliberate move to gather feedback from developers and users before the official version — and Tencent says that's exactly what happened. According to the model card, the team collected feedback from more than 50 product teams after the late-April preview, fixed issues in task execution and interaction, and scaled up its post-training pipeline. The architecture is unchanged: 295B total parameters, 21B active per forward pass via top-8 routing across 192 experts, a 3.8B-parameter multi-token prediction (MTP) layer for speculative decoding, and a 256K context window.

What changed is behavior. Tencent's positioning is that the full release significantly outperforms similar-size models and rivals flagship open-source models with two to five times the parameters. That 'two to five times' framing makes sense for where this model is aimed — and it invites a direct comparison with the current open-weight coding leader, GLM-5.2.

Tencent's blind test favors Hy3 over GLM-5.1, but GLM-5.2 still owns coding Tencent's headline evaluation is a blind human study rather than a leaderboard. Arguing that public benchmarks don't tell the full story, the company ran a blind test with 270 experts across disciplines working on real-world workflows, collecting 312 valid comparisons, in which Tencent reports that Hy3 scored 2.67 out of 4 against GLM-5.1's 2.51 — with the clearest advantages in frontend development, CI/CD, and data and storage work. The choice of opponent matters.