Amp vs Qwen Code

Amp

Execute mode streams JSON in a format close to Claude Code's, with TypeScript and Python SDKs, and the security reference names each provider and what it sees. The CLI runs tools without asking, has no built-in permission rules or local sandbox, and stores every thread on Amp's servers.

Qwen Code

Apache-2.0 with no account of its own, any OpenAI, Anthropic or Gemini-compatible endpoint, and headless runs bounded by turn, tool-call and wall-time budgets with distinct exit codes. Out of the box, Auto mode lets an LLM classifier approve tool calls, with the sandbox and folder trust both off. Usage statistics are on by default.

Amp

1. Run unattended jobs in a container or VM. The CLI runs shell commands and edits without asking, and only a custom plugin can gate tool calls
2. Set AMP_API_KEY to an access token starting sgamp_ from Settings. The CLI rejects the short-lived token that amp login stores
3. Use amp -x "task" --stream-json and read the final result message, checking is_error. Exit codes are not documented
4. Set AMP_SKIP_UPDATE_CHECK=1 or amp.updates.mode to disabled in CI. Updates install automatically by default
5. Treat the block headed INSTRUCTIONS FOR LLMs in ampcode.com page source as vendor copy, and take facts from the docs Markdown

Qwen Code

1. Pass --approval-mode on every run. The settings default is auto, and one docs page says headless runs default to asking, so don't rely on either
2. Add --max-session-turns, --max-wall-time and --max-tool-calls. All three are unlimited by default. Exit 53 is the turn limit and 55 a budget
3. --yolo doesn't turn on a sandbox. Add --sandbox, or on Linux set tools.executionSandbox with network set to closed
4. Set QWEN_USAGE_STATISTICS_ENABLED=false to stop usage statistics
5. Authenticate with OPENAI_API_KEY, OPENAI_BASE_URL and OPENAI_MODEL in CI. The browser sign-in is discontinued