TRAE China Version: Real Data on Free Model Speed

Let me start with the conclusion: if you use the free models in TRAE China’s version, they will be slower than custom paid models (even when comparing the same model).

The free models are mainly slower in 3 aspects:

  1. When processing large tasks, free models may display a prompt: “Model has reached the maximum number of thinking attempts. Please type ‘continue’ to get more results.” When this happens, you need to manually type “continue” to proceed. As shown in Figure 1. Figure 1

  2. Calling free models requires queuing; this was already mentioned in the previous blog. As shown in Figure 2. Figure 2 Additionally, during task processing, there’s a chance you’ll need to queue again.

  3. The DeepSeek V4 Pro model has think mode enabled by default, with a thinking depth of around 200, which makes it slower when processing large tasks. To illustrate this point, I recorded the execution time from my own project.

The specific execution time for a task was: begin 11:34 / end 12:24. As shown in Figure 3.

Figure 3

But here’s what I found: the free Qwen3.6 Plus model is significantly faster than the paid DeepSeek V4 Pro model when handling large tasks — and I mean much faster. Moreover, the free Qwen3.6 Plus model has shorter queue times.

Those Are the Real Data and Facts. Now Here’s My Opinion: DeepSeek Is a Great Company, and Its Pricing and Services Truly Benefit the Public

I can understand that DeepSeek is still in development, which is why there are some limitations.

But the technology and services they provide are deeply imbued with a sense of human mission; based on this sense of mission and responsibility, this company is contributing to increasing the average intelligence of humanity.

This sense of mission and responsibility, in my personal view, stems from the founder’s simple beliefs and character. In short, it’s not about money — it’s about serving the people.

A Brief About Me

I’ve worked at NetEase Games, Baidu, Tencent (8 years), and Meituan (nearly 7 years), leading large-scale R&D projects and managing teams of 100+ engineers.

Currently, I’m pursuing entrepreneurship in the AI field.

Why? The world runs on uncertainty — staying in corporate roles too long breeds addiction to certainty. Starting an AI venture is like setting sail into uncharted waters.

Feel free to reach out: mailto:HummingbirdLabs@outlook.com.