mini-swe-agent vs openinterpreter
The 100-line agent from the SWE-bench team: >74% on SWE-bench Verified with no tools but bash, no config sprawl — the reference minimal harness, adopted by Meta, NVIDIA and Ramp. — versus — Terminal coding agent optimized for low-cost open models — a Rust Codex fork with switchable harness emulation (claude-code, kimi-code, qwen-code…), ACP support and Codex SDK compatibility.
Standalone open coding agents at two extremes: mini-swe-agent is the 100-line research baseline; Open Interpreter is a production CLI tuned per-model for cheap open weights.
| mini-swe-agent | openinterpreter | |
|---|---|---|
| Stars | 6.3k | 68k |
| Forks | 866 | 5.8k |
| Language | Python | Rust |
| License | MIT | Apache-2.0 |
| Last activity | 6 days ago | 8 days ago |
| Topics | coding, agents | coding, agents |
| Curated connections | 6 | 3 |
mini-swe-agent — the curator's take
The existence proof that most harness complexity is optional: the team that built SWE-bench and SWE-agent asked what a 100x simpler agent loses — the answer is almost nothing (>74% Verified), which is why it became the standard baseline harness for benchmarking models (Ramp's SWE-bench, DeepSWE — where it beats Claude Code and Codex as a harness). Read it to understand agents; use it to evaluate models fairly. NOT a daily driver: no MCP, no skills, no IDE plumbing — by design. If you're choosing a tool to ship features with, this is the control group, not the product.
openinterpreter — the curator's take
The harness-emulation bet is unique: instead of one house style, it reimplements the provider-recommended harness per model (Kimi, Qwen, DeepSeek…), which is exactly what cheap open models need to perform. Codex-SDK-compatible, so switching costs one line. When NOT: if you live on Claude or GPT frontier models, their native CLIs stay ahead of the emulation; and the project has reinvented itself before (the original Python open-interpreter era) — expect direction changes.