
A 295B-parameter MoE language model for agentic and productivity tasks.
Visit WebsiteThe Bottom Line
Entry price
Free, no paid tier
Biggest pro
Outperforms models with 2-5x more total parameters on agentic and productivity tasks.
Biggest con
Requires high-memory GPUs (e.g., H20-3e) for deployment due to large total parameter count.
TL;DR - Tencent Hy3
- 295B-parameter MoE model with 21B active parameters, rivaling models 2-5x larger.
- Significant improvements in agentic capabilities and task productivity across coding, office work, and financial modeling.
- Enhanced reliability with reduced hallucination rate (from 12.5% to 5.4%) and better multi-turn conversation tracking.
What is Tencent Hy3?
Pros & Cons
Pros
- Outperforms models with 2-5x more total parameters on agentic and productivity tasks.
- Reliability improvements in tool calls and output formats make it production-ready.
- Open-source weights available on multiple platforms, including Hugging Face and ModelScope.
Cons
- Requires high-memory GPUs (e.g., H20-3e) for deployment due to large total parameter count.
- FP8 quantized model available, but it still demands substantial hardware resources.
Preview
Key Features
Pricing
Tencent Hy3 is completely free to use with no hidden costs.
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Tencent Hy3 FAQ
How does Hy3 handle long-context conversations without losing track of intent?
What agent scaffoldings are compatible with Hy3, and how consistent are the results?
How was Hy3 evaluated beyond public benchmarks?
What hardware is recommended for serving Hy3?
Is there a quantized version of Hy3 available?
What context window size does Hy3 support?
How does Hy3's reasoning mode work for different task complexities?
What specific productivity tasks does Hy3 excel at?
Source: huggingface.co