Trae finally launched a paid version
Opened Trae today and suddenly saw “Upgrade to Pro” in the top right corner. Wow, it finally has a paid version! Wow, the price is great! $7.5/month — that's way cheaper than cursor and GitHub copilot!
Opened Trae today and suddenly saw “Upgrade to Pro” in the top right corner. Wow, it finally has a paid version! Wow, the price is great! $7.5/month — that's way cheaper than cursor and GitHub copilot!
Void is an open-source AI code editor that can replace Cursor. During testing, it showed some gaps in understanding and missing features when generating HTML pages, but with config tweaks and a different model (such as Qwen2.5-Coder-32B) it can produce quite good results.

Qwen3 is really fast — 0.2 seconds to first token, 55 TPS, more than 220% faster than the previous QwQ-32B...

Recently, the updated Trae added support for MCP, opening up a whole new way to use it — for programmers, this is another form of Manus. Then right after, I got my hands on something new that makes digital life better: a **Fellou** that puts the browser to work for me, automatically running deep research and boosting efficiency. Both are shining examples of homegrown tech.
When using QwQ-32B, the MLX version throws this error during chat: “Error rendering prompt with jinja template: Error: Parser Error: Expected closing statement token. OpenSquareBracket !== CloseStatement.”, which you need to fix by modifying the jinja template. The gguf version doesn't have this problem. After the fix it ran successfully, as shown in the image.
Trae's China version now supports DeepSeek, and it outperforms Claude3.5-Sonnet in some scenarios. QwQ-32B's performance is close to R1, making it a good fit for local deployment. If Manus goes mainstream, it will upend existing technology, and future AI will need cloud resources to support multimodal operations and agent collaboration.
It's Chinese New Year, and everyone is talking about DeepSeek. Ruirui wants to play "Who's the Spy" but can never round up enough people, so I built an AI-powered "Who's the Spy" game bot that calls an LLM to generate character descriptions and voting strategies — but I ran into problems like unstable model output and formatting errors. After tweaking the model and the prompts over and over, I finally got the basic functionality working, and the whole process was full of funny mistakes and challenges.
I'd like to recommend AnythingLLM. Combined with LM Studio, it can run local large models as a private AI assistant. I'll share my experience trying it out for document processing and studying traditional Chinese medicine. The results are only so-so for now, but the journey from zero to one is well worth it.