腾讯 Hy4 发布：Artificial Analysis 智能指数得 35 分，为中国实验室第二名模型
腾讯混元出了新模型 Hy4，跑分和 Grok 4.7 打平，编码能力超过 DeepSeek 和 Kimi，但幻觉率 89% 有点高，价格倒是便宜。
腾讯混元发布 Hy4，是今年早些时候 Hy3 的后继版本，在 Artificial Analysis Intelligence Index v5 得 35 分，与 Grok 4.7 (xhigh) 持平，比 Claude Haiku 5.5 (max) 低 1 分。在中国实验室模型中，Hy4 排名第二，仅次于得 46 分的 Kimi K3.1 Pro。智能体编码方面，Hy4 在 FrontierCode 2.0 得 31%，超过 DeepSeek V4.1 Flash 1017 (max) 的 28% 和 Kimi K3.1 Pro 的 25%。定价为每百万输入/输出 tokens $0.834/$2.501，单位智能成本比 Grok 4.7 便宜 10 倍。短板是幻觉率高达 89%，而 Kimi K3.1 Pro 为 37%。
Hy4 from Tencent scores 35 on the Artificial Analysis Intelligence Index v5 and is the #2 model from a China-based AI lab
Hy4 is the latest model from @TencentHunyuan and is the successor to Hy3 released earlier this year. It scores 35 on the Artificial Analysis Intelligence Index v5, equal with Grok 4.7 (xhigh) and 1 point behind Claude Haiku 5.5 (max). Hy4 is the #2 model from a China-based AI lab, behind only Kimi K3.1 Pro, which scores 46. Hy4 is priced at $0.834/$2.501 per 1M input/output tokens.
Key takeaways:
➤ Hy4 excels at agentic coding tasks. Hy4 scores 31% on FrontierCode 2.0, compared to 32% for Claude Fable 5.1 (max). It is the leading model from a China-based AI lab, with DeepSeek V4.1 Flash 1017 (max) scoring 28% and Kimi K3.1 Pro scoring 25%. On Terminal-Bench 4.0, it scores 37%, the fourth-highest score among models from China-based AI labs
➤ Hy4 outperforms its peers on knowledge and reasoning. Hy4 achieves accuracy of 50% on AA-Omniscience v1.1, 1 point ahead of Kimi K3.1 Pro, but has a high hallucination rate of 89% compared to Kimi K3.1 Pro’s 37%. On HLE-Diamond, it scores 33% compared to Kimi K3.1 Pro’s 37%
➤ Hy4 offers a competitive Capability vs. Cost trade-off compared to to peers. With a Cost per Intelligence Index Task of $0.78, Hy4 (35) is 10-times cheaper than Grok 4.7 (xhigh, 35) and 13-times cheaper than Qwen3.8 Max (0902) (34) but almost twice as expensive as Claude Haiku 5.5 (max, 36)
Other model details:
➤ Context window: 1 million tokens
➤ Pricing: $0.834/$2.501 per 1M input/output tokens. Cache reads $0.042 per 1M tokens
➤ Multimodality: Text and image input, with text output
