| Specification | Value |
|---|---|
| Total parameters | 295 billion |
| Active parameters per token | 21 billion |
| MTP layer parameters | 3.8 billion |
| Number of layers | 80 transformer layers + 1 Multi-Token Prediction layer |
| Attention heads | 64 |
| Context window | 256K tokens (262,144) |
| Architecture | Dense-attention, sparse-FFN MoE |
The model supports configurable reasoning modes — a direct "no-think" mode plus low/high chain-of-thought modes for complex tasks . Tencent describes it as a "hybrid fast-and-slow-thinking model"
.
Within its first week, Hy3's total API call volume grew more than 68× compared to Hy2, the previous-generation model . A Chinese-language report from Sina Finance notes that Hy3's growth trajectory "continued the upward trend of the Hy3 preview version but with a steeper slope"
.
Exact total token volume figures beyond the weekly OpenRouter tallies were not published in the sources reviewed, but the demand surge was dramatic enough to overload Tencent's compute infrastructure. On July 8 (two days after launch), WorkBuddy's inference computing resource consumption peaked, with afternoon queue rates exceeding 50% . Tencent had to urgently allocate additional compute capacity, announcing service restoration on the morning of July 9
.
The Hy3 Preview had already accumulated 7.7 trillion tokens on OpenRouter between April 23 and May 12, according to Tencent's Q1 2026 earnings materials .
Hy3 is released under the Apache 2.0 license with no geographic restrictions . The full model weights are available on Hugging Face at
tencent/Hy3 .
Tencent's strategy with Hy3 is explicitly about agents over model size. As Forbes covering the launch noted, Tencent is betting that an efficiently activated MoE model (21B active of 295B total) at dramatically lower cost can rival much larger dense-model flagships . Key benchmarks cited include:
The Hy3 Preview launched April 23, 2026 as the first model built on Tencent's completely rebuilt pre-training infrastructure . It was described as the "first model trained on Tencent's rebuilt infrastructure" and delivered significant improvements over Hy2 in complex reasoning, instruction-following, in-context learning, code generation, and agent capabilities
. The Preview held OpenRouter's top usage slot for three consecutive weeks
, and the full release amplified that momentum — with total calls growing 68× over Hy2 versus an already strong Preview growth rate
. Between Preview and GA, Tencent's team refined the model through global developer feedback and across its own massive product ecosystem, with measurable improvements: hallucinations dropped from 12.5% to 5.4% and commonsense reasoning errors fell from 25.4% to 12.7%
.
Key takeaway: In its first ~10 days, Hy3 achieved 68× call volume growth vs. Hy2, became the #1 model by call volume on OpenRouter, overloaded Tencent's own compute infrastructure due to demand, captured 60% of WorkBuddy custom-model users, and demonstrated enterprise agentic improvements (90% task success rate, 34% faster execution). This builds directly on the Hy3 Preview's momentum, which had already dominated OpenRouter rankings since late April.