Gray vs Devin: which should you use?

Last updated

Short answer

Choose Devin if you want a managed cloud software agent that picks up issues and returns PRs in its own sandboxed environment. Choose Gray if you want a minimal MIT harness on your own machine — your models, your keys, your data — including always-on jobs.

GrayDevin
What it isMinimal, always-on AI harness: one Rust binary, open source (MIT)Cognition's proprietary cloud software-engineering agent
Where it runsYour own machine or serverDevin's cloud: each task gets a managed environment
How you use itTerminal, headless mode, cron and app connectionsAssign issues and tasks; get PRs back — web, Slack and API
ModelsAny OpenAI-compatible provider with your own API key; local models through Ollama; Claude Pro/Max and ChatGPT plans through official pluginsManaged by Cognition, with model access set by your plan
DataConversations, sessions and credentials stay on your machine under ~/.grayCode and runs live in Devin's cloud
PriceFree (MIT); you pay your model provider. Hosted Voyager plan $77/month, not yet openFree tier ($0, limited quotas); Pro $20/month and up

Is Gray a Devin alternative?

Only if your work is local and interactive: Gray runs on your machine with your own keys and no managed cloud. For fully delegated issue-to-PR work in a managed environment, Devin is the product; Gray is the bring-your-own-everything counterpart.

Which keeps code off third-party servers?

Gray — sessions and credentials stay under ~/.gray, and pairing it with a local model through Ollama keeps code fully on your hardware. Devin tasks run in Cognition's cloud; see Privacy.

When should you choose Devin instead?

Choose Devin for delegating complete tasks — issue in, reviewed PR out — where a managed cloud environment, integrations and support matter more than local control.

Sources

Competitor details are taken from the sources above as of the date at the top of this page. Products change quickly — if something here is out of date, open an issue on GitHub.