Tencent HY4 Emerges as a Leading Open-Weight AI Model

Tencent has quietly launched its most powerful open-weight AI model yet — the HY4. Packing a staggering 770 billion parameters and a one million token context window, this model is setting new benchmarks in coding, reasoning, and long-horizon tasks while keeping costs competitive.

What Makes Tencent’s HY4 Stand Out?

The HY4 is not your average AI model. Boasting 770 billion parameters with a sparse activation of only 49 billion, it strikes a balance between scale and efficiency. Its massive one million token context window is specially designed for tackling complex, long-sequence workflows. Tencent clearly targets challenging areas like software engineering, document-intensive office tasks, scientific research, and agentic AI work.

While the model competes closely with others like the Kimi K3, GLM 5.3 Flash, and Opus 5, its benchmark performance reveals clear strengths in debugging, reasoning, and agent tasks. Although it doesn’t dominate every chart, HY4 holds its ground and even outperforms several rivals in key areas.

Affordability Meets Performance

One of HY4’s more surprising strengths is its efficiency. Originally a 1.5 terabyte behemoth, Tencent compressed it down to around 200 GB using novel quantization techniques that barely impact performance. This shrinks storage and inference costs dramatically without sacrificing benchmark scores.

Pricing-wise, HY4 charges 83 cents per million input tokens and $2.50 per million output tokens, an aggressive undercut compared to other open models. This makes it especially attractive for developers building apps that require fast, large-scale text generation and analysis on a budget.

Real-World Use Cases: From Games to Document Analysis

HY4’s potential shines brightest in demonstrations like creating a full Spider-Man game prototype. In about six hours and nine iterations—around 5.6 million tokens—the model crafted a detailed 3D game at a cost of just $13. For open-weight AI, that’s impressive both in cost and creative output.

The model also excels in web development tasks, generating complex scenes such as 3D simulations of the International Space Station with more consistent camera work and lighting than competitors like GLM 5.3 Flash. In fact, for this ISS simulation, HY4 delivered the highest quality scenario at a reasonable cost of $1.30 and completion time of under two hours.

Comparing HY4 to Other Leading AI Models

Side-by-side tests with models like the JLM 5.3 and Qwen 3.8 Flash reveal a tight race. For outputs requiring visual richness—like shader effects and dynamic lighting—the JLM 5.3 can slightly outperform HY4. But HY4’s textures and creativity often come out on top, as seen in 3D zombie game generation where it handled complex foliage and darker moods more cleanly with fewer glitches.

HY4 isn’t always the fastest or cheapest, but it often produces the best final quality, especially for tasks with complex logical consistency over long sequences. It’s a model designed not just to create, but to maintain coherent, reasoned outputs over extended interactions.

Open Access and Developer Friendly

Tencent has released HY4 under the Apache 2.0 license, offering full weights for those who want to run it locally with options for lower-bit quantization. Developers can also access an API through the Tensor Cloud and test HY4 on platforms like the World of AI benchmark and VIVE Point.

With its unique efficiency and pricing, HY4 is carving out a niche for developers and researchers who need powerful AI without the prohibitive costs common in the space. It might not replace all leading open models overnight, but its blend of speed, scale, and affordability makes it a compelling choice to experiment with.

What This Means for AI Innovation

Tencent’s approach with HY4 highlights a shift in AI model development: focusing on massively scaled sparse models that can tackle tough problems while reducing computational overhead. The extended context length unlocks new possibilities for long-range reasoning and complex task management. For developers, AI researchers, and enterprises, HY4 presents an exciting new tool to explore aggressive, high-level workflows.

While the Kimi K3 still offers leading visual style and design taste, HY4 offers a surprisingly effective alternative at faster speeds and lower costs. Testing both will help determine the right fit depending on project demands.

Tencent deserves credit for quietly pushing open-source AI boundaries with HY4. Its emergence may not come with fanfare, but the model’s capabilities promise to shape the future of open AI applications for real-world complexity and scale.