Tencent's Hy4: A Power User Tool or Just Another AI Mirage?

Is the Hy4 model ready for your workflow?

Tencent recently launched Hy4, its latest attempt to bridge the gap between language models and actual software execution. Unlike its predecessor, Hy4 features native vision capabilities and the ability to operate desktop applications, such as CAD software or game engines, by chaining commands sequence-by-sequence.

According to the company, the model was optimized for high-stakes environments like finance and office automation. Tencent claims that in tests involving 200 finance professionals, Hy4 outperformed other Chinese models, including Deepseek V4.1 Flash and Kimi K3.1 Pro. However, this internal optimism contrasts sharply with independent data from Artificial Analysis, which places Hy4 in the middle of the pack—tied with Grok 4.7 and significantly behind the current market leaders.

The accuracy trap

The most critical takeaway for professional users is the model's reliability gap. While Tencent highlights its success in specific document-handling tasks, independent testing reveals a concerning tendency to fabricate information. When faced with questions outside its training data, Hy4 hallucinates 89% of the time instead of admitting it does not know the answer.

This makes the tool risky for research-heavy workflows where factual integrity is non-negotiable. While the company claims a reduced hallucination rate through a revamped search feature, the raw performance on factual accuracy benchmarks remains a bottleneck for enterprise adoption.

How to test the model

If you want to evaluate whether Hy4 fits your specific technical requirements, you don't need to wait for the open-weight release. The model is currently accessible via:

• Tencent Cloud: The primary enterprise gateway for API access.
• OpenRouter: A flexible way to test the model alongside other frontier providers.
• Yuanbao: Tencent’s consumer-facing chatbot app.

Note that Tencent maintains a pricing structure of approximately $0.83 per million input tokens and $2.50 per million output tokens. Given its current performance profile, it is best suited for internal, highly structured tasks where you can verify the output, rather than open-ended research.

Verdict: who should use it?

Hy4 is not a general-purpose replacement for your current Claude or GPT-4 workflows. Its strength lies in specialized, repetitive tasks—such as game engine configuration or specific document automation—where Tencent has provided custom-tuned training data.

If your work involves complex coding, advanced math, or long-form research, the model's current performance gap compared to GPT-6.1 Sol or Claude Opus 5.5 is significant. Use it as a specialized tool for specific automation pipelines, but maintain strict human-in-the-loop oversight for any output involving factual data.