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Tool profile · AI Coding Assistants

opencode

The terminal-native agent with the largest open-source community in the category.

93
sovereignty

opencode (MIT) is a coding agent that runs in your terminal, with a desktop app in beta and IDE extensions alongside it. It is deliberately provider-agnostic — 75+ providers via the AI SDK and Models.dev, including Ollama, LM Studio and any OpenAI-compatible local endpoint — and it ships two built-in agents: a full-access `build` agent and a read-only `plan` agent for exploring a codebase before anything is allowed to change it. It is now the most-starred project in this space at roughly 191k GitHub stars, maintained by Anomaly after the repository moved from `sst/opencode` to `anomalyco/opencode`. The optional opencode Zen gateway sells curated, benchmarked models pay-as-you-go and includes some free ones; using your own provider keys stays free.

OPEN SOURCEMITSELF-HOSTLOCAL-FIRST
LicenseMIT
PricingFree and open source (MIT) — you pay your own provider. The optional opencode Zen gateway is pay-as-you-go, with some free models; your own API keys cost nothing extra.
Open sourceYes
Self-hostableYes
Local-first dataYes

What it does well

  • +MIT and provider-agnostic by design — 75+ providers, plus Ollama, LM Studio or any OpenAI-compatible local endpoint
  • +The read-only `plan` agent lets you scope work before the agent can touch a file
  • +Terminal-first, so it works over SSH on a server or a modest machine
  • +The largest community in the category and daily commits

Where it falls short

  • Terminal-first is a genuine adjustment coming from an editor-integrated agent; the desktop app is still beta
  • No inline autocomplete — a different tool for a different job than Cursor's Tab
  • Ownership moved from SST to Anomaly; the MIT licence means no practical risk, but it's worth knowing
  • Large configuration surface (providers, models, agents) — more to learn than picking from a dropdown

Hardware note

The client is a single binary and runs comfortably on modest hardware, including over SSH. Running the model locally is the demanding part: budget ~24 GB VRAM or a 32 GB+ unified-memory machine for a 30B-class quantised coding model, and expect a capability gap against a frontier cloud model on multi-step agent work.

opencode as an alternative to

Where opencode shows up in our comparisons, and how it ranked.

opencode head-to-head

Straight comparisons against the tools people weigh it against.

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