Post
3554
The rebuilt Hunyuan HY3 Preview is here!
I tested it on all the tricky scenarios where most LLMs usually face-plant—and guess what? It didn’t flop.
295B total params, 21B active params, 256K context window. Built on MoE architecture, it delivers trillion-parameter-level performance with a much smaller footprint. Long-context capabilities get a massive upgrade.
Agent abilities stand out this time: tool calling, workflow orchestration, and autonomous planning are far more stable in real business scenarios. AI PPT generation in Tencent Docs is also significantly smoother and more reliable.
Real-world tests on WorkBuddy show first-token latency down 54%, success rate over 99.99%, and an Agent workflow that ran continuously for 495 steps.
Its Coding Agent achieved top-tier results on both SWE-Bench Verified and Terminal-Bench 2.0
Now open-sourced on GitHub, HuggingFace, and ModelScope. Available on TokenHub at just 1.2 RMB per million tokens.
I tested it on all the tricky scenarios where most LLMs usually face-plant—and guess what? It didn’t flop.
295B total params, 21B active params, 256K context window. Built on MoE architecture, it delivers trillion-parameter-level performance with a much smaller footprint. Long-context capabilities get a massive upgrade.
Agent abilities stand out this time: tool calling, workflow orchestration, and autonomous planning are far more stable in real business scenarios. AI PPT generation in Tencent Docs is also significantly smoother and more reliable.
Real-world tests on WorkBuddy show first-token latency down 54%, success rate over 99.99%, and an Agent workflow that ran continuously for 495 steps.
Its Coding Agent achieved top-tier results on both SWE-Bench Verified and Terminal-Bench 2.0
Now open-sourced on GitHub, HuggingFace, and ModelScope. Available on TokenHub at just 1.2 RMB per million tokens.