My personal experience with the LuChen SDK is that it is easy to get started with, usable immediately after registration, and reasonably priced.

For individual users who only need to fine-tune models, there is no need to worry about machine provisioning, instance initialization, or storage management. Users only need to initialize the training configuration, provide a dataset, and specify the model. Overall, it is very easy to start using and highly practical—essentially reaching a “one-click launch” level of usability.

Based on the provided examples, I have tried LoRA training for Qwen3-8B on both the LuChen SDK and Tinker AI training platform. In terms of ease of use, the LuChen SDK is comparable to Tinker, and its documentation and examples are even more user-friendly. The example code on the official website may need some corrections, but the examples in the cookbook can be run directly.

Using only the README in the cookbook, I was able to roughly learn how to build a fine-tuning pipeline. I can monitor the training process either locally in the terminal or online through Weights & Biases (wandb). The separation between compute and development environments effectively lowers the infrastructure barrier for users.

At the moment, training speed still needs improvement. When fine-tuning Qwen3-8B with LoRA, each step takes more than 10 seconds on the LuChen SDK, whereas on Tinker it only takes about 3–4 seconds.

In the current era of rapid breakthroughs in high-quality base models such as Seedance and Nano-Pro, I have seen more and more creators using AI across different platforms. Creators are producing AI-generated images, short videos lasting only a few seconds, long videos lasting tens of minutes, and even various forms of music.

I strongly feel that AI is entering everyday life, reaching more households and becoming part of people's daily creative workflow.

At present, generative AI still has a certain barrier to entry, especially for tasks involving specific styles or targeted content generation. However, we are already seeing a large amount of impressive creative work.

I believe that in the future, everyone will want to personalize strong base models to create content in their own style. Therefore, fine-tuning will become a widespread need. Lowering the barrier to fine-tuning—until anyone, even those without AI expertise, can personalize their own models—would be extremely meaningful. The LuChen SDK is a product that made me feel that this barrier is being lowered.

As some people in the community have said about AI-generated content: "Although AI still has clear shortcomings, it has become the best way for small creators to turn written scripts into videos. Without AI video tools, these works might only exist as text articles, and people like me would never get to see them."

AI is currently giving everyone the ability to turn their ideas into high-quality, shareable content, and the cost continues to decrease. Therefore, lowering the barrier to fine-tuning, expanding accessibility to models, and enabling greater personalization are extremely important directions for the future.