opencode vs claw-code

Two of the top coding agents and assistants, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.

11st of 21 in Coding agents and assistants

opencode

Terminal coding agent with build and plan modes

79 out of 100
22nd of 21 in Coding agents and assistants

claw-code

Rust CLI coding agent harness, built from source

77 out of 100

Verdict

opencode ranks higher, 79 to 77. Of the 5 score parts we measure for both, opencode leads on 2, claw-code on 1 and 2 are even.

  • Adoptionopencode leads by 3 points, 99 to 96: close to even.
  • FreshnessEven at 100.
  • Maintenanceopencode leads by 17 points, 92 to 75: a wide gap.
  • Easy to runEven at 50.
  • Agent-readyclaw-code leads by 40 points, 70 to 30: a wide gap.

Pick opencode if you are

Developers wanting an open terminal coding agent

  • MIT license; installable from npm, Homebrew, Scoop, Chocolatey, pacman, mise and Nix
  • Plan agent denies file edits and asks before bash, for safe codebase exploration

Pick claw-code if you are

Rust-comfortable developers inspecting or building a CLI coding agent harness

  • Rust workspace builds to a single `claw` binary with a `doctor` check
  • Supports local OpenAI-compatible backends: Ollama, llama.cpp, vLLM
opencode vs claw-code: score parts and facts
What we compareopencodeclaw-code
Score parts, out of 100
Adoption99, widely used96, widely used
Freshness100, active100, active
Maintenance92, healthy75, fair
Easy to run50, easy50, easy
Agent-ready30, minimal70, partly
Facts from GitHub and the README
Stars213k195k
LicenseMIT (permissive)MIT (permissive)
Last commitOct 2026Oct 2026
Last releaseOct 2026Oct 2026
LanguageTypeScriptRust
DockerNoYes
GPUNot neededNot stated
arm64 or Apple SiliconMentionedMentioned

opencode

Runs an AI coding agent in the terminal with two built-in agents: build (full access) and plan (read-only, asks before running bash), plus a general subagent for multi-step searches. Installs via a curl script, npm, Homebrew, Scoop, Chocolatey, pacman, mise or Nix, and ships a beta desktop app for macOS, Windows and Linux. For developers who want an open, configurable coding agent.

Who it is for: Developers wanting an open terminal coding agent

Strengths

  • MIT license; installable from npm, Homebrew, Scoop, Chocolatey, pacman, mise and Nix
  • Plan agent denies file edits and asks before bash, for safe codebase exploration
  • Desktop app (beta) for macOS, Windows and Linux alongside the terminal UI

Weaknesses

  • README covers install only; providers, config and server mode are in external docs
  • No Dockerfile or compose file in the repo
  • Desktop app is still beta
  • no GPU

claw-code

Claw Code is a Rust implementation of the `claw` CLI agent harness, with the workspace in `rust/` and commands such as `claw prompt`, an interactive session, and `claw doctor` as a health check. It authenticates with API keys (Anthropic, OpenAI, others), and the docs cover local OpenAI-compatible providers such as Ollama, llama.cpp and vLLM. The README describes the repo as an agent-managed exhibit and points users who want to run work to LazyCodex or Gajae-Code.

Who it is for: Rust-comfortable developers inspecting or building a CLI coding agent harness

Strengths

  • Rust workspace builds to a single `claw` binary with a `doctor` check
  • Supports local OpenAI-compatible backends: Ollama, llama.cpp, vLLM
  • MIT license; PowerShell-first Windows install docs alongside Linux and macOS
  • Mock parity harness and workspace test suite via `cargo test --workspace`

Weaknesses

  • Build from source only; `cargo install claw-code` installs a deprecated stub
  • README says it is not the serious production project
  • Claude subscription login unsupported; API key required
  • No ACP/Zed daemon yet; `claw acp serve` only returns status
  • Docker + Compose
  • Needs Rust toolchain (cargo), API key (Anthropic, OpenAI or compatible provider)
  • Models: Anthropic API, OpenAI API, OpenAI-compatible local servers (Ollama, llama.cpp, vLLM)

More in Coding agents and assistants

Building with these?

We help teams pick an open-source AI stack and run it in production. Client work never changes a rank.