Plandex vs QwenLM/qwen-code
Side-by-side comparison of two AI agent tools
Short answer
- Plandex has had no commit in 12 months; QwenLM/qwen-code is actively maintained (3,463 commits in the last 90 days).
- QwenLM/qwen-code is growing faster: +465 GitHub stars in the last 30 days vs +85 for Plandex.
- Pick Plandex for: open source AI coding agent. Pick QwenLM/qwen-code for: an open-source AI coding agent that lives in your terminal.
From GitHub data refreshed daily.
Plandexopen-source
Open source AI coding agent. Designed for large projects and real world tasks.
Q
QwenLM/qwen-codeopen-source
An open-source AI coding agent that lives in your terminal.
Metrics
| Plandex | QwenLM/qwen-code | |
|---|---|---|
| Stars | 15.7k | 28.3k |
| Star velocity /mo | 84.6031746031746 | 465 |
| Commits (90d) | 0 | 3.5k |
| Releases (6m) | 0 | 10 |
| Overall score | 0.2698555571014626 | 0.8642094222460844 |
Pros
- +Exceptional context handling with 2M+ token capacity for understanding large, complex codebases
- +Purpose-built for real-world, multi-file projects rather than simple single-file tasks
- +Open-source with self-hosting options, providing full control over your development environment
Cons
- -Terminal-based interface may not appeal to developers who prefer GUI tools
- -Potentially overkill for simple, single-file coding tasks or quick fixes
- -Requires setup and configuration that may be complex for casual users
Use Cases
- •Large-scale refactoring projects that touch dozens of files across a codebase
- •Implementing comprehensive features that require changes across multiple components and layers
- •Modernizing legacy codebases with systematic updates and architectural improvements
FAQ
- Which is more popular, Plandex or QwenLM/qwen-code?
- QwenLM/qwen-code has more GitHub stars (28,273 vs 15,688).
- Which is more actively developed, Plandex or QwenLM/qwen-code?
- QwenLM/qwen-code had more commits in the last 90 days (3,463 vs 0).
- Should I use Plandex or QwenLM/qwen-code?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.