Tencent Releases Hy3: 295B-Parameter MoE Model with 21B Active Parameters, Apache 2.0 Licensed
Score
75提供了详细的参数规模、激活参数、上下文长度和开源信息，但缺少完整基准测试对比。
内容结构清晰、数据准确，但未引用官方技术报告或论文，依赖博客转载。
Apache 2.0许可和免费试用降低了使用门槛，对需要高性价比大模型的公司和研究者实用价值极高。
2026年7月6日发布的最新模型，时效性极佳。
来源Simon Willison是知名技术博主，信息源自腾讯官方Hugging Face页面和OpenRouter，但非一手官方新闻稿。
Base 83 × T2 Source weight ×0.9 = 75
Curation line 70Selected
Why selected
High information gain, but lack of detailed technical report and full benchmark evaluation keeps score moderate.
AI commentary
「The highlight of this model is 'doing more with less'—only 21B active parameters challenging 70B+ models proves the efficiency of MoE. It's a boon for small and medium teams with limited budgets who want to run large models. However, independent benchmarks are lacking; I recommend testing it on OpenRouter yourself.」
Quick overview
Tencent's Hy Team releases Hy3, a 295B-parameter Mixture-of-Experts model with 21B active parameters and 3.8B MTP layer parameters. Building on feedback from 50+ products since the April preview, post-training with higher-quality data yields performance surpassing similar-sized models and rivaling flagship open-source models with 2-5x parameters. Context length 256K. Model weights 598GB (FP8 quantized: 300GB). Free on OpenRouter until July 21.
- Scale: 295B total parameters, 21B active, 3.8B MTP layer parameters, MoE architecture.
- Performance: Outperforms similar-sized models, rivals flagship open-source models with 2-5x parameters.
- Context length: 256K tokens.
- License: Apache 2.0, free on OpenRouter until July 21.
Full text
Showing the source text; the full translation is being generated.
Hy3 is a 295B-parameter Mixture-of-Experts (MoE) model with 21B active parameters and 3.8B MTP layer parameters, developed by the Tencent Hy Team. Following the Hy3 Preview launch in late April, we gathered feedback from 50+ products and scaled up post-training with higher quality data. Today, we introduce Hy3, which outperforms similar-size models and rivals flagship open-source models with 2-5x parameters. It also shows significant gains in utility across various products and productivity tasks.
The full-sized model is 598GB on Hugging Face, and the FP8 quantized one is 300GB. The context length is 256K.
It's available for free on OpenRouter until July 21st. I had it "Generate an SVG of a pelican riding a bicycle" there and got this:
Tags: ai, generative-ai, llms, pelican-riding-a-bicycle, llm-release, ai-in-china
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