DevinvsClaude Code

2 agents, 2 evaluations — 0 community and 2 editorial — compared across overall score, task fit, reliability, cost, ease of setup, and drift over time.

Current verdict: Claude Code currently leads Devin by 2.0 points on Ruling's 10-point scale; confirm the top-review context before shortlisting.

ruling.so/compare/devin-vs-claude-code

Scorecard

Winners are highlighted only when comparable review-derived scores exist.

2 evaluations considered

Overall

Weighted aggregate verdict across the review.

7.6/10

3.8/5 source average.

9.6/10

4.8/5 source average.

review avg
Task fit

How well the agent matches the job users hired it for.

8.0/10

4.0/5 source average.

9.8/10

4.9/5 source average.

review avg
Reliability

Consistency, uptime, and repeatability under real workflows.

7.0/10

3.5/5 source average.

9.2/10

4.6/5 source average.

review avg
Ease of setup

How quickly teams can get from signup to useful output.

8.2/10

4.1/5 source average.

8.6/10

4.3/5 source average.

review avg
Cost efficiency

Whether the results justify the seat, usage, or platform cost.

6.0/10

3.0/5 source average.

7.8/10

3.9/5 source average.

review avg
Drift score

How well quality holds up over longer sessions and releases.

7.4/10

3.7/5 source average.

9.4/10

4.7/5 source average.

review avg

At a glance

A truthful, data-backed summary of where each agent stands today.

Devin

Cognition · Coding Agents

Devin was the first publicly announced "AI software engineer," capable of planning and executing full engineering tasks across a sandboxed environment with browser, terminal, and code editor. While early demos generated enormous hype, real-world users report it excels at well-scoped tasks but struggles with ambiguous requirements. Controversy around its benchmark claims makes it one of the most debated agents on the platform.

Best signalUseful for scoped engineering tickets, but not a replacement engineer

Claude Code

Anthropic · Coding Agents

Top score

Claude Code is Anthropic's CLI-native agentic coding tool, running directly in the terminal with deep filesystem and shell access. It reads the entire codebase context and can autonomously edit files, run tests, and commit code — making it a favourite among power users who prefer a terminal-first workflow. Claude Code is widely regarded as the most capable agent for complex, multi-file refactors.

Best signalThe most capable terminal-native coding agent we benchmarked

Pricing and specs

Static facts from the Ruling catalog, not prototype estimates.

Pricing
Paid
Usage Based
Price details
Free; Pro $20/mo; Max $200/mo; Teams $80/mo minimum with $40/mo full seats; Enterprise custom
Included with Claude Pro ($20/mo monthly, $17/mo annual) and Max (from $100/mo); API token billing also available
Model backbone
Proprietary (Cognition)
Claude Sonnet 5, Claude Opus 5, Claude 4.x family
Setup complexity
Easy
Easy
Catalog facts
Verified Aug 21, 2026
Verified Aug 21, 2026
Evaluations
1
1

Pricing and model availability change quickly. Ruling shows the latest catalog value we have verified from official sources; confirm on the vendor site before purchasing.

Top review for each

Most helpful published review per agent, pulled from current Ruling data.

Browse all reviews
Top review↓ most helpful
RE
Ruling Editorial — Engineering
Ruling editorial benchmark · < 1 month

Useful for scoped engineering tickets, but not a replacement engineer

Ruling editorial benchmark: Devin is strongest when the ticket is narrow, the repo is accessible, and success can be checked with clear tests or acceptance criteria. It is less reliable when the task requires product judgment or deep organizational context. The product is important to benchmark because it defines the autonomous-software-engineer category, but buyers should evaluate output quality against cost carefully.

24 found helpfulRead →
RE
Ruling Editorial — Engineering
Ruling editorial benchmark · 1-6 months

The most capable terminal-native coding agent we benchmarked

Ruling editorial benchmark: Claude Code is excellent when the workflow starts in the terminal and the task benefits from reading files, editing multiple paths, running tests, and iterating with explicit approval. It feels less like autocomplete and more like a supervised engineering partner. Teams should still budget for token usage and require human review before merging generated changes.

28 found helpfulRead →

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