Status basis: npm_downloads_7d gained 3070 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Accelerating npm_downloads_7d gained 3070 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Anomaly daily change 23202.0 is 3.9 standard deviations from this entity's own prior mean (148.9±5963.2, baseline excludes this point) — unusual, not necessarily adoption
- Accelerating npm_downloads_7d gained 3070 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Accelerating npm_downloads_7d gained 3070 in the last 3d vs 562 in the 3d before (ratio 5.5x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 3070 in the last 3d vs 562 in the 3d before (ratio 5.5x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to -25175 per 3d from 12572 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -15801 per 3d from 12572 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 18434 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 12572 in the last 3d vs 8169 in the 3d before (ratio 1.5x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 18434 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 12572 in the last 3d vs 8169 in the 3d before (ratio 1.5x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 18434 in the last 3d vs 6271 in the 3d before (ratio 2.9x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 8169 in the last 3d vs 1475 in the 3d before (ratio 5.5x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 8169 in the last 3d vs 1475 in the 3d before (ratio 5.5x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to 1475 per 3d from 25816 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -115 per 3d from 25816 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -2245 per 3d from 25572 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 25816 in the last 3d vs 1445 in the 3d before (ratio 17.9x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to -2245 per 3d from 25572 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 25816 in the last 3d vs 1445 in the 3d before (ratio 17.9x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 25572 in the last 3d vs 3588 in the 3d before (ratio 7.1x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 12346 in the last 3d vs 3588 in the 3d before (ratio 3.4x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to -6516 per 3d from 12219 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -6516 per 3d from 12219 (<= 40% of the prior window)
| Machine-callable | — | unknown | — |
| Open source | 1 | verified | 1 quote(s) |
| Self-hostable | — | unknown | — |
| Bring your own key | — | unknown | — |
| Autonomy level | 4 | inferred | 4 quote(s) |
| Pricing model | — | unknown | — |
| Integrations | telegram | inferred | 1 quote(s) |
“Unknown” means we have not verified it — it is not a “no”. Hard filters never treat unknown as false.
It embeds AI deeply into the terminal workflow, offering a frictionless, 'invisible' development experience that pushes the boundaries of AI-native coding tools.
Evidence quotesverbatim, from the product’s own materials
“public GitHub repository (README fetched)”— structural
“file issues, submit PRs, review code, and run tests”— readme
“Dynamic workflows, zero setup.”— readme
“actively iterating on itself”— readme
“IM bots (Telegram / DingTalk / WeChat / Feishu).”— readme
FAQ
What is qwen-code?
qwen-code is an open-source AI coding agent that runs directly in the terminal, enabling developers to write, debug, and refactor code using natural language.
What does qwen-code do?
Enable code generation, debugging, and refactoring directly in the terminal using natural language to boost development speed.
Why does qwen-code matter?
It embeds AI deeply into the terminal workflow, offering a frictionless, 'invisible' development experience that pushes the boundaries of AI-native coding tools.
How much does qwen-code cost?
Free
Is qwen-code free?
Yes — qwen-code has a free tier. Pricing as stated on its own page: Free
Is qwen-code open source?
Yes — qwen-code is open source.
What does qwen-code integrate with?
telegram
How popular is qwen-code?
As tracked by KanonAgent: 28.8k upvotes (first indexed 2026-07-20).
What are the best qwen-code alternatives?
Similar AI agents tracked by KanonAgent: deepseek-harness, gemini-cli, Codédex, LLM Gateway, oh-my-openagent, goose.