The Quen 3 model from Alibaba Cloud has demonstrated impressive performance, often surpassing even the state-of-the-art models like DeepSeeq. The largest 235 billion parameter Quen 3 model performs on par with or better than DeepSeeq on a variety of benchmarks that truly matter, including Arena Hard, AE24, and others.

Interestingly, Quen 3 also offers smaller 30 billion parameter models that rival the capabilities of GPT-4, but at a much smaller size. These models excel across a range of benchmarks, including Arena Hard, AMY, math, coding, and more.

One unique feature of Quen 3 is its "thinking mode," which allows the model to continue improving its abilities and intelligence as it processes the task. This dynamic thinking approach is not yet available in other open-source models, giving Quen 3 an edge in reasoning capabilities.

The author's personal experience with the Quen platform has been very positive, with the model demonstrating impressive performance on tasks like generating visually appealing infographics, rebuilding web pages in HTML, and simulating an ant colony with pheromone trails. While the model may not always outperform state-of-the-art models like Claude, its open-source and free-to-use nature make it a highly compelling option, especially for those looking to leverage advanced AI capabilities without significant cost.

Quen 3, Alibaba's latest large language model, has impressed with its strong performance across a variety of benchmarks. However, the true test lies in its real-world capabilities. Let's dive in and explore how Quen 3 handles artifact generation and multimodal tasks.

Artifact Generation: Visually Appealing Infographics

When tasked with turning a table into an interactive, visually appealing infographic using HTML, CSS, and JavaScript, Quen 3 delivered a surprisingly polished result. The model's output was more visually striking than the infographic generated by the renowned Claude 3.7 model, showcasing Quen 3's strong design sensibilities.

Multimodal Capabilities: Rebuilding Websites

To further test Quen 3's abilities, we challenged the model to rebuild a given web page as a standalone HTML file. While the resulting design was not as visually impressive as Claude 3.7's output, Quen 3 was able to successfully recreate the core functionality of the webpage, demonstrating its competence in multimodal tasks.

Simulating an Ant Colony

When asked to write a P5.js script that simulates an ant colony with pheromone trails and basic AI rules, Quen 3 provided a functional simulation, though it fell short of the level of detail and interactivity achieved by Claude 3.7's impressive ant colony simulation.

Industry Research and Insights

Quen 3's ability to conduct comprehensive industry research and provide detailed insights was put to the test. The model was able to generate a well-structured research report, drawing from various data sources and accurately addressing the key points outlined in the prompt. While there were a few instances of potential hallucinations, the overall quality and relevance of the information provided were impressive.

Multimodal Capabilities: Image and Video Generation

Quen 3 also showcased its multimodal capabilities by generating images and videos based on prompts. The image generation results were decent, though not as polished as professional tools. The video generation, while low-resolution and slightly laggy, was a surprising and welcome addition to the model's capabilities.

Overall, Quen 3 has demonstrated a strong performance across a range of tasks, often rivaling or even surpassing the capabilities of established models like Claude 3.7. Its ability to handle artifact generation, multimodal tasks, and industry research highlights the impressive progress made in open-source AI models. As Quen 3 continues to evolve, it will be exciting to see how it further challenges the boundaries of what's possible in the world of large language models.

Quen 3, Alibaba's latest large language model, has surprised many with its impressive performance. Benchmarked against state-of-the-art models like GPT-3 and DeepSeeq, Quen 3's 235 billion parameter mixture of experts model performs on par or even better in key areas.

The smaller 30 billion parameter Quen 3 models also rival GPT-4 in capability, while being much more lightweight. Quen 3 introduces a "thinking mode" that allows the model to reason and improve its abilities over time, a feature not yet available in other open-source models.

When tested against the popular Claude model, Quen 3 demonstrated strong multi-modal capabilities. It was able to generate visually appealing infographics and simulate an ant colony with pheromone trails, tasks that Claude also excelled at. However, Claude's web page recreation was more polished in terms of front-end design.

The true strength of Quen 3 lies in its comprehensive set of features, including image and video generation, voice/video chat, and advanced search and analysis capabilities - all available for free. This level of functionality and accessibility is unprecedented for an open-source language model.

While not perfect, Quen 3 has the potential to disrupt the AI industry with its impressive performance and diverse capabilities. For users looking to leverage powerful language models without the cost or limitations of proprietary solutions, Quen 3 is a compelling option worth exploring.

Quen 3, Alibaba's latest large language model, has demonstrated impressive capabilities in deep research and analysis. Here are the key highlights:

1. Comprehensive Research: The model was able to quickly search through multiple sources and provide an executive summary on the AI agents market, covering key findings such as projected growth, niche vertical solutions, and common customer complaints.

2. Verifiable Data Sources: When checking the links provided in the research report, the information matched the summarized points, indicating the model's ability to extract relevant and accurate data.

3. Handling Hallucinations: While the model did seem to hallucinate one data point, it was able to provide verifiable information for the majority of the research findings, showcasing its ability to distinguish factual data from potential hallucinations.

4. Versatility: In addition to text-based research, Quen 3 also demonstrated capabilities in image and video generation, including the ability to create images and short videos based on prompts.

5. Multimodal Capabilities: The model's integration of voice chat and video chat features further enhances its versatility, allowing for more interactive and engaging interactions.

Overall, Quen 3 has proven to be a powerful and comprehensive AI assistant, capable of conducting deep research, generating multimedia content, and engaging in multimodal interactions. Its free and open-source nature makes it an attractive option for those seeking advanced AI capabilities without the cost barriers.

Quen 3, Alibaba's latest large language model, has surprised me with its impressive image and video generation capabilities. Despite being an open-source model, it can produce visually appealing and creative outputs.

When I asked Quen 3 to generate an image of a "crusanium thaw manipulated to resemble the head of an eagle", the result was quite decent. The model was able to create a coherent image that matched the prompt, even though the text overlay was not perfect.

Furthermore, Quen 3 impressed me with its ability to generate a short video of a "huge elephant leisurely drinking water by the Clear River using its long trunk to scoop up water and spray it on its body to ward off the heat." The video, while low-resolution and a bit laggy, was still a remarkable feat for a free, open-source model.

What's even more surprising is that Quen 3 also offers voice and video chat capabilities, allowing users to have real-time conversations and collaborate. This level of multimodal functionality is quite impressive and sets Quen 3 apart from other open-source language models.

Overall, Quen 3's image and video generation, along with its other features, make it a compelling and free alternative to more expensive, proprietary AI assistants. While there is room for improvement, the model's capabilities are already quite remarkable, and I encourage users to try it out while it's still available for free.

Quen 3, Alibaba's latest large language model, has surprised me with its impressive capabilities, including its voice and video chat features. These features allow for more interactive and engaging conversations, taking the AI assistant experience to a new level.

The voice chat functionality enables real-time conversations, allowing you to speak with the AI and receive responses through voice. This can be particularly useful for those who prefer talking over typing, making the interaction more natural and efficient.

While the voice chat does not provide the ability to directly search the internet, you can collaborate with the AI to find information online together. This collaborative approach enhances the user experience and ensures that the AI remains focused on the task at hand.

Furthermore, the video chat feature adds a visual component to the interaction, enabling you to have face-to-face conversations with the AI. This can be beneficial for tasks that require visual cues or demonstrations, such as providing feedback on content creation or discussing complex topics.

Overall, Quen 3's voice and video chat features are a testament to the model's advanced capabilities and its ability to provide a more immersive and personalized user experience. These features set Quen 3 apart from other AI assistants and showcase the potential of this powerful language model.