codewhale vs oh-my-openagent
Two of the top projects in Coding agents and AI editors, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
codewhale
Terminal coding agent in Rust that works with 40+ model providers
oh-my-openagent
Terminal coding agent with multi-model routing and git-backed memory
Verdict
codewhale ranks higher, 94 to 92. Of the 4 score parts we measure for both, codewhale leads on 1, oh-my-openagent on 2 and 1 is even.
- Adoptionoh-my-openagent leads by 3 points, 96 to 93: close to even.
- FreshnessEven at 100.
- Maintenancecodewhale leads by 14 points, 97 to 83.
- Agent-readyoh-my-openagent leads by 15 points, 85 to 70: a wide gap.
Pick codewhale if you are
Developers who want a model-agnostic terminal coding agent with audit trails
- /receipts lists changed files, commands run, web and MCP calls, and approvals
- Plan, Work and Operate modes with Ask, Auto-Review and Full Access permissions
Pick oh-my-openagent if you are
Developers who want a terminal coding agent that orchestrates multiple models
- Native binary installer for macOS, Linux and Windows; also on npm and bun as omo-ai
- Mixes frontier and cheap models, with a tuned system prompt per model
| What we compare | codewhale | oh-my-openagent |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 93, widely used | 96, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 97, healthy | 83, healthy |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 41.2k | 70.9k |
| License | MIT (permissive) | custom license (read the license) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Oct 2026 | Nov 2026 |
| Language | Rust | TypeScript |
| Docker | Yes | No |
| GPU | Optional | Not needed |
| arm64 or Apple Silicon | Mentioned | Mentioned |
codewhale
Codewhale is a terminal coding agent that reads a repository, edits files and runs shell commands until a task is done or it needs input. It supports more than 40 built-in providers, any OpenAI-compatible endpoint, and local models through Ollama, vLLM or SGLang, with DeepSeek as the default. It also has a headless exec mode, a local web UI, a PR review command and an ACP server for editors.
Who it is for: Developers who want a model-agnostic terminal coding agent with audit trails
Strengths
- /receipts lists changed files, commands run, web and MCP calls, and approvals
- Plan, Work and Operate modes with Ask, Auto-Review and Full Access permissions
- One engine behind the TUI, exec, local web UI, Runtime API and ACP over stdio
- Reads AGENTS.md; opt-in import of CLAUDE.md and Cursor rules; supports MCP, skills, hooks
Weaknesses
- Telemetry is on by default; aggregate counts are sent until you disable it
- No OS sandbox on Windows, and Full Access disables the sandbox everywhere
- Some features, such as the one-step /undo and terminal workbar, are only in unreleased 0.10.2
- exec --auto defaults to Full Access with no shell sandbox
- GPU optional
- Docker
- Needs Git repository, Provider API key or local runtime (Ollama, vLLM, SGLang), bubblewrap (optional, Linux sandbox)
- Models: DeepSeek, Anthropic, OpenAI, Google, Mistral
oh-my-openagent
OmO is an `omo` command-line coding agent built on senpi, a fork of pi. It routes tasks to different models, signs in with Claude, ChatGPT, Kimi and GLM subscriptions, and can fan a job out into a graph of parallel agents with `mass ulw`. Memory is kept as markdown files in a git repository, and a small model nudges the main agent based on past sessions.
Who it is for: Developers who want a terminal coding agent that orchestrates multiple models
Strengths
- Native binary installer for macOS, Linux and Windows; also on npm and bun as omo-ai
- Mixes frontier and cheap models, with a tuned system prompt per model
- Memory stored as markdown in a git repo, so it is inspectable and versionable
- `omo setup` migrates provider keys, MCP servers and skills from the OpenCode edition
Weaknesses
- Custom license (SUL-1.0), not a standard OSI license
- In-app bug reports can include session transcripts and device details
- Computer use is marked experimental
- Install is a curl-piped shell script from a project-run domain
- no GPU
- Needs Model provider account or API keys
- Models: Claude, ChatGPT, Kimi, GLM
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