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Devin Cloud vs GLM (Z.ai)
A plain-English comparison to help you choose between them.
Both answer the same shortage, more coding volume than engineers to absorb it, by opposite routes: Devin does the work instead of your team, while GLM makes the client your team already uses cheap enough to carry the volume themselves. Pick Devin when the backlog is well specified and the constraint is hands, since it plans, writes, tests and opens the pull request in its own environment and runs sessions in parallel, provided you have the senior review capacity its output assumes. Pick GLM when your engineers want to keep their editor, their workflow and their keybindings and change only what feeds them, taking a flat-rate coding plan for routine volume with open weights available to self-host when the hosted API's jurisdiction is a question you have to answer.
Side by side
- Summary
Devin is Cognition's autonomous software engineer: hand it a well-scoped task and it plans, writes, tests and opens the pull request, working in its own environment rather than your editor.
- Best for
- Well-scoped tasks executed end to end to a PR
- Parallel sessions multiplying senior engineers
- Bulk migrations and dependency upgrades
- Cost
- Paid only
- Ease
- Openness
- Hosted service
- Data
- Devin works inside your repositories and environments under the access you grant; scope credentials like you would a contractor's.
- Summary
GLM is Z.ai's coding-first model family, sold less as a new tool than as a change to what powers the one you already have.
- Best for
- Flat-rate coding subscription
- MIT-licensed GLM-5.2 open weights you can self-host
- A 1M-token context for large-codebase work
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Runs privately (self-hostable)
- Data
- GLM's hosted terms point to Singapore while its developer is Chinese-founded, a jurisdiction point to weigh before routing real code or prompts through it. Self-hosting the open weights removes that question entirely: the model runs on infrastructure you control, and nothing leaves it.
Pricing
- Devin Cloud
$20·$200·from $80·Custom
Prices as of August 2026.
- Pro
- $20per monthusage billed at API rates
- Max
- $200per monthusage billed at API rates
- Teams
- from $80per monthusage billed at API rates
- Enterprise
- Price on applicationno list price published
- GLM (Z.ai)
$12.60·$56·$117.60$79.20/user·$169.20/user
Prices as of August 2026.
- Lite
- $12.60per monthbilled annually; $18 per month if billed monthly
- Pro
- $56per monthbilled annually; $80 per month if billed monthly
- Max
- $117.60per monthbilled annually; $168 per month if billed monthly
- Standard Seat
- $79.20per user, per monthbilled annually; $88 per user per month if billed monthly
- Premium Seat
- $169.20per user, per monthbilled annually; $188 per user per month if billed monthly
Common questions
Are these really alternatives, or complements?
Alternatives, though the layers differ. GLM feeds coding clients such as Claude Code, so it complements those; it does not feed Devin, which runs its own closed environment. A team with a backlog and no extra headcount genuinely chooses between delegating the work to an agent and making its existing engineers cheaper to run at volume.
What does each approach cost you beyond money?
Devin costs review capacity. Its plans carry an included usage allowance and meter what runs past it, with cost scaling to task size and complexity, so vague tasks become expensive lessons and every pull request still needs a senior pair of eyes. GLM costs either a jurisdiction answer or an infrastructure project, since its hosted terms point to Singapore while the developer is Chinese-founded, and self-hosting the open weights removes the question by handing you the operations instead.
Which work suits each one?
Devin suits the well-specified backlog: bulk migrations, dependency upgrades, repetitive fixes and scoped features a senior engineer can define precisely and review efficiently. GLM suits routine daily coding volume inside a familiar client, with the honest working pattern being a frontier seat retained alongside it for ambiguous specs and sustained multi-agent sessions.
Related comparisons
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Where to start
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Tool facts last checked August 2026