Version 26.05.01 Calibration STEM and Agentic Languages EN ZH HI AR RU JA KO NL FR ES Model Size 182.05 GB Contact Email — Model Introduction — Stronger Agent Capabilities — More Reliable Product Experiences — Benchmark Appendix — News — Model Links — Quickstart — Deployment — vLLM — SGLang — Finetuning — Quantization — License — Contact Us Building on Hy3 Preview, we further improved the quality and diversity of post-training data while scaling up RL training. Hy3 shows solid gains across reasoning, agentic, and long-context tasks, competitive with much larger flagship models. In productivity scenarios such as coding, office work, financial modeling, frontend design, and game development, Hy3 has made remarkable progress and can now serve as a reliable, cost-effective model option. We don’t think public benchmark scores tell the full story. So we ran a blind evaluation with 270 experts using tasks from their work, and Hy3 scored 2.67/4, outperforming GLM-5.1 at 2.51/4. The advantage was most substantial in frontend development, data & storage, and CI/CD tasks. Model usefulness is not fully captured by benchmarks. Based on extensive product feedback, we identified and…
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Автор: cyankiwi
Теги: hy_v3, hunyuan, hy3, moe, conversational, endpoints_compatible, compressed-tensors
Лайков: 4 | Загрузок: 179
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
