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Hy3 preview: A Rebuilt Hunyuan, a 21B-Active MoE, and a New Reasoning Receipe
imnotkitty
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imnotkitty
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liked a model about 2 months ago
deepseek-ai/DeepSeek-V4-Pro reacted to wangbuer999's post with 🔥 2 months ago
Testing AI controlling AI with Hy3 Preview I barely lifted a finger the whole time.
One-click deployment of Hermes on WorkBuddy took some time with a few rounds of adjustments, and I finally got it up and running smoothly
Only minor issue was setting up Supermemory it was a bit slow on the uptake. I had to go over simple steps several times, guiding it patiently like teaching a kid.
The experience of AI orchestrating AI is absolutely incredible. started running Agents with Hunyuan right after its release, and it actually works perfectly.
295B parameters, 21B active parameters, with direct access to TokenHub now great cost-performance ratio too
Honestly, I used to get stuck on all kinds of environment configurations when deploying Agents locally. Using Hy3 to take command made the whole process way more streamlined. repliedto their post 2 months ago
https://huggingface.co/spaces/tencent/Hy3-preview is out: an open-weights MoE reasoning model.
✅ 295B total / 21B active / 256K context
✅ Fused fast-and-slow thinking in a single model
✅ First model trained on Hunyuan's rebuilt pretraining + RL infra (Feb → Apr)
Benchmarks:
👉 SWE-Bench Verified, Terminal-Bench 2.0, BrowseComp, WideSearch — competitive results, particularly strong on agentic tool use
👉 Top score on Tsinghua's 2026 Spring math PhD qualifying exam
👉 Strong context-learning and instruction-following on Tencent's CL-bench / CL-bench-Life
More details can be found in my article: https://huggingface.co/blog/imnotkitty/hy3-previewOrganizations
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imnotkitty
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