So Tencent just launched Hy3, their newest open source AI model, and it brings some pretty interesting upgrades. If you are a developer, product engineer, or a founder trying to run an efficient workflow without burning a massive hole in your wallet, this is a model you definitely need to look at.
What makes this model special right out of the gate is that Tencent decided to ship the final version under a fully open Apache two point zero license. That means you can use it for commercial projects without jumping through legal hoops or worrying about restrictions. On top of that, they focused heavily on making it reliable for real world apps instead of just trying to chase high scores on arbitrary leaderboards. They actually cut the model's hallucination and common sense error rates right in half compared to the older preview versions. That makes it way more stable when you are trying to handle long, complex conversations or trying to force it to output strict data formats like clean JSON.
The Tech Under the Hood
Let us talk about how this thing is actually built. Hy3 uses a mixture of experts architecture. It has a massive two hundred and ninety five billion total parameters, but it only activates twenty one billion parameters at a time for any given token.
This is the sweet spot for modern open weights models. By only triggering a small slice of its total brain power at once, it stays incredibly fast and responsive while still giving you the deep reasoning and performance of a giant three hundred billion parameter model.
Tencent also packed a two hundred and fifty six k context window into this version. If you have ever tried to paste an entire coding file or a massive chunk of project documentation into a standard AI window only to hit a context wall, you know how annoying that is. With two hundred and fifty six k tokens, you can comfortably feed it large sections of your codebase or massive documents without the model losing its memory or getting confused halfway through.
Let us Look at the Benchmarks
To see how smart this model actually is, we can look at how it handles developer specific and agent driven tasks.
- SWE-bench Pro: This benchmark tests how well an AI can jump into a real, complex GitHub repository and resolve actual software engineering issues. Hy3 scores fifty seven point nine percent here. That is a solid number that puts it right behind GLM five point two and keeps it competitive with top tier closed models.
- Terminal Bench two point one: This is a tough benchmark that measures command line execution, bash scripting, and direct system control capabilities. Hy3 hits seventy one point seven percent on this test, which means it completely outperforms models like DeepSeek V4 pro when it comes to navigating a terminal and running system tasks.
- MCP Atlas Public: This benchmark evaluates how well a model can interact with the Model Context Protocol, which is essential if you are building autonomous agents that need to use external tools, query databases, or call APIs. Hy3 scores seventy nine point one percent, beating out several major open source alternatives in the ecosystem.
The takeaway from the data is pretty clear. Tencent built this model specifically for builders who need a model that can write code, run terminal commands, and handle agentic tool workflows without constantly breaking down.
Where Can You Use It?
If you want to test Hy3 out for yourself, you have two great options depending on what kind of setup you prefer.
1. Tencent AI Studio
You can go straight to the official website at aistudio.tencent.com. This is Tencent's official developer platform. It gives you an easy way to test the model directly inside your web browser, read through the technical documentation, and manage your API keys if you want to build something directly inside their native cloud ecosystem.
2. OpenRouter
Another fantastic option is OpenRouter. They have already listed the model on their platform, making it incredibly easy to connect to your existing developer workflows and AI code editors. The best part is that you can use Hy3 completely for free on OpenRouter right now during its initial launch period.
What Happens When the Free Tier Ends?
Eventually, the promotional free tier on OpenRouter will wind down, and you will have to pay for the tokens you use. While the finalized official pricing for this specific version has not been fully locked in by Tencent yet, it will likely match the pricing structure of the preview version.
If it stays the same, the regular pricing will look like this:
- Input Tokens: Zero point zero six three dollars per million tokens.
- Output Tokens: Zero point twenty one dollars per million tokens.
When you break that down, cost wise, it is exceptionally budget friendly. Running a massive two hundred and ninety five billion parameter model for fractions of a penny per request is an incredible value, especially compared to the steep monthly subscription fees or high API costs of premium closed source alternatives.
Setting Up Hy3 in VS Code
If you want to take advantage of this free tier right now and bring Hy3 directly into your coding environment, setting it up in VS Code is incredibly straightforward.
First, you need to head over to the OpenRouter website, log into your account, and go to your dashboard to create a new API key. You can give it any description you want. For example, I am just going to name mine VS Code. Once the key is generated, copy it to your clipboard.
Next, open up your VS Code editor. You will want to open your model selection menu or your specific AI copilot extension settings. Look for the option that says manage models or configure providers. In this menu, you need to add OpenRouter as your active API provider. Hit enter, and then paste the API key that you just copied from your OpenRouter dashboard.
Once your key is connected, VS Code will pull in the available models. To keep your interface clean and fast, you can go ahead and hide all the unnecessary models you do not plan on using and keep only the models you want. For this setup, I am just going to keep Hy3 visible.
Finally, open your main model picker one more time and select Tencent Hy3. Now everything is fully connected and ready to go. You can open up your chat sidebar, highlight a piece of code, or use inline generation to ask it a question. When you test it out with a coding problem, you will see that it responds quickly, gives a really good answer, and handles debugging tasks incredibly well.
Final Thoughts
This approach gives you a completely free way to leverage a top tier open weights model directly inside your IDE. If you are tired of paying for expensive monthly premium copilot plans or you just want to experiment with alternative open source architectures that compete with the biggest names in the industry, Hy3 is worth adding to your stack.
If you want to see a full, step by step visual walkthrough of this setup and see the model in action, I have put together a complete guide on my channel. You can watch the full video right here on YouTube:Tecent Hy3 Video
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