Alibaba is coming for Claude...

Fireship • 2025-07-23 • 4:04 minutes • YouTube

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Alibaba’s Quen 3 Coder: A New Challenger in AI-Powered Coding

In a major breakthrough for AI-driven programming, Chinese tech giant Alibaba has unveiled Quen 3 coder, an openweight, long-horizon mixture of experts agent coding model that is already making waves in the developer community. Released on July 23rd, 2025, Quen 3 coder is the first openweight model to rival the programming prowess of Claude 4, currently regarded as the leader in AI coding tools.

What Makes Quen 3 Coder Stand Out?

Massive Training with a Code-Heavy Diet

Quen 3 coder was trained on an astonishing 7.5 trillion tokens, with 70% of that data being code—a volume far beyond what even the most seasoned developers have seen in a lifetime. To put it into perspective, this is equivalent to a billion times more code than a developer with 50 years of experience.

Advanced Training Techniques

The model’s training process is highly sophisticated, leveraging long horizon reinforcement learning across 20,000 parallel environments. This means Quen 3 coder learns by actively solving real-world coding problems, executing, and testing code simultaneously—like a coding boot camp with thousands of tireless graduates all working in unison.

Impressive Performance Benchmarks

Benchmarks reveal that Quen surpasses notable models like Kimmy K2 and GPT-4.1, and approaches the elite performance level of Claude 4, despite having a significantly smaller model size. Smaller models are crucial because they require less computational power and electricity, making them more efficient for deployment.

Unmatched Context Window

One of Quen 3 coder’s most striking features is its massive 256,000 token context window, which can stretch up to 1 million tokens. This capacity can easily encompass entire codebases of startups, including all their technical debt, enabling it to understand and work with large, complex projects seamlessly.

Quen CLI: Command-Line Power for Developers

Alongside the model release, Alibaba introduced a new CLI tool, forked from the open-source Gemini CLI. This tool fully exploits Quen 3 coder’s agentic capabilities, allowing developers to run, execute, and test code directly from the command line. This integration marks a significant step toward making AI coding assistants more practical and accessible in everyday programming workflows.

Practical Considerations: Accessibility and Usage

Despite its groundbreaking capabilities, Quen 3 coder’s full 480 billion parameter version demands enormous resources—requiring tens or hundreds of thousands of dollars in GPU infrastructure and substantial electricity costs. Hence, running it locally on a typical laptop is unrealistic.

Most users will likely access Quen 3 coder via API keys from cloud providers and use the new Quen CLI to interact with the model. This cloud-based approach democratizes access while maintaining the heavy computational lifting on powerful servers.

The AI Coding Landscape: Quen vs. Claude and Others

While Quen 3 coder represents a significant leap for open coding models, it remains to be seen if it can dethrone Claude 4’s dominance. To truly topple Claude, a new model must be not only open and affordable but also deliver a decisive leap in coding capabilities.

OpenAI, despite recent setbacks like talent losses and delays in open model releases (possibly due to competition from Chinese models like Quen), continues to make strides. Notably, OpenAI and Google both recently achieved gold medals in the International Mathematical Olympiad, showcasing their AI’s prowess in complex problem-solving—another domain relevant to advanced coding skills.

Boost Your Coding Today with Code Rabbit

For developers eager to harness AI for better coding now, Code Rabbit offers a powerful solution. Their free VS Code extension provides advanced code reviews directly in your editor, plus a new “fix all with AI” feature that applies all review suggestions automatically through your AI coding agent of choice.

Code Rabbit saves you from manually addressing each review comment, freeing up time to focus on writing more code—flaws and all! It integrates seamlessly with VS Code and popular forks like Cursor and Windsurf. You can download it for free using the link below.

Final Thoughts

Alibaba’s Quen 3 coder pushes the boundaries of open AI models in coding, combining enormous training data, cutting-edge reinforcement learning, and a massive context window to challenge industry leaders. While it may not unseat Claude 4 just yet, it signals a new era of powerful, accessible AI coding assistants.

As AI continues to evolve, developers have more tools than ever to enhance their productivity and creativity. Whether through giants like Quen 3 coder or practical extensions like Code Rabbit, the future of programming looks increasingly collaborative between humans and intelligent machines.

Try Code Rabbit today and supercharge your coding workflow!

This has been The Code Report. Thanks for reading, and happy coding!

📝 Transcript (124 entries):

Yesterday, Chinese company Alibaba dropped a brand new openweight long horizon mixture of experts agent coding model named Quen 3 coder. And amazingly, it's the first openweight model that matches the programming performance of Claude 4, the undisputed leader of AI vibe coding tools at the present time.

Not only is the Quen 3 coder model open, but they also just released a brand new CLI tool forked from the recently open source Gemini CLI that can take advantage of all the models agentic properties like the ability to run, execute, and test your code from the command line. That's terrifying news for any programmer still left with a job, but mathematicians are also on life support right now because both Google and OpenAI just achieved gold medals in the International Mathematical Olympiad.

In today's video, we'll take a look at the latest AI breakthroughs and find out if Quen 3 coder can actually compete with Claude 4. It is July 23rd, 2025, and you're watching the code report.

Just last week, the open model scene got a big upgrade with the Chinese Kimmy K2, but now Quen 3 coder pushes things even further. The model was trained on 7.5 trillion tokens with a 70% code ratio.

In other words, it's seen a billion times more code than the average developer with 50 years of experience. They even use their previous model to clean up noisy training data, the highly meta process where AI basically determines which data to use to train itself. When it comes to the training process, they use something called long horizon reinforcement learning across 20,000 parallel environments. The model actually tries to solve real world problems in real environments where it's executing and testing code. You can think of Quen's training infrastructure like a coding boot camp with 20,000 graduates all working on the same problem simultaneously, except they never get tired, never argue, and never ask, "Is this a breaking change?" And the end result speaks for itself in these benchmarks. Based on this benchmark, Quen is outperforming Kimmy and GPT4.1 and almost on par with Claude 4, but doing so with a much smaller model size, which is important because the bigger the model, the more electricity and GPUs you need to run it.

What's also really impressive about Quen 3 coder is that it has a 256,000 token context window that can stretch up to 1 million tokens. For reference, that's enough to hold the entire codebase of most startups and all of their technical debt. Quen 3 coder is an openweight model, but if you think you're going to run it locally on your laptop, it's time for a reality check. To harness the full girth of the 480 billion parameter version, you would need tens of thousands, if not hundreds of thousands of dollars worth of GPUs along with a large wallet to pay the electricity bill. Realistically, to try it, you'd want to get an API key from a cloud provider, then hook it up to the new Quen CLI tool, which again is a fork of the Gemini CLI. Overall, this does appear to be a big leap forward for open coding models. But I doubt that it will make much of a dent in Claude's dominance in the coding world. To be Claude, a company needs to release a model that's not only open and inexpensive, but that surpasses Claude's capabilities by a significant margin.

Like OpenAI was recently supposed to release its own Open model, but that's been delayed with the rumor for the delay being that these Chinese models would absolutely crush it. That's just one of many L's taken by OpenAI recently, like Zuck gutting all of their talent. But OpenAI did get a big win a few days ago when they achieved a gold medal in the International Mathematical Olympiad. What's funny though is that they made a dick move by announcing this before the closing ceremonies of the event in order to overshadow Google and the press, who also achieved gold medal level performance. However, that ended up backfiring because it just made OpenAI look desperate. But if you want to write really good code with AI, you need to check out Code Rabbit, the sponsor of today's video. Their free VS Code extension gives you advanced code reviews right in your editor. And their new fix all with AI feature passes all of Code Rabbit's review context directly to the AI code agent of your choice is so it can make all the changes for you.

This saves you from needing to click on each review comment yourself, giving you more time to write even more broken code like a true artisan. Code Rabbit is free to use in the IDE and works seamlessly with VS Code and forks like Cursor and Windsurf. Download it for free with the link below to try it out. This has been the code Report. Thanks for watching and I will see you in the next one.

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