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VerdictPal · editorial desk · 2026VerdictPal
Compare · Head-to-head

Pick two cards. See the diff.

Stat bars are editorial heuristics, methodology linked — not a fake benchmark leaderboard. Put two dossiers side by side and see where each one breaks.
CardsModels

Compare · Card A / Card B·Head-to-head

CursorvsWarp

Both sit close together in the Build & code set; editorial fit is within four points. Cursor wins on value for money; Warp wins on source quality, privacy controls, and speed. For the canonical workflow, pick Cursor. Use Warp when its niche specifically wins above.

Cursor · avg
65
wins 2 of 16
Warp · avg
73
wins 11 of 16
Fields differ
13
of 16 dossier rows
Receipts
20
sources + bench notes

Checked 2026-06-07 · Cursor·Checked 2026-06-09 · Warp

Dossier fields

Sixteen fields, side by side.

No.FieldCursorWarp
01Status · Editorial quality gateFlagshipSolid
02Editorial fit · 0–100 score81 / 10084 / 100
03CategoryBuild & codeBuild & code
04Primary surfaceProsumer SaaSLocal app
05Modalities
  • Code
  • Text
  • Code
  • Text
06Role in a stackAI-native code editor and agentic refactor workspaceAI-native terminal and agentic development workspace
07Best for
  • Developers already living in VS Code who want Tab, Chat, and Agent in one editor
  • Repo-wide refactors where multi-file diffs must be reviewed before merge
  • Teams that need SAML/OIDC, centralized billing, usage analytics, team-wide Privacy Mode, and admin controls
  • Students eligible for one free Pro year who can still run tests and read generated code
  • Developers who want terminal-native AI help without leaving command-line workflows
  • Teams experimenting with local and cloud coding agents, third-party CLI agents, BYOK/BYO tooling, and shared command workflows
  • Power users who value modern terminal UX plus agent orchestration
  • Organizations that need SOC 2 / ZDR-positioned controls before using AI in terminal workflows
08Avoid if
  • You cannot enable Privacy Mode or get approval before sending sensitive code to AI providers
  • You need deterministic flat pricing with no usage-based overage exposure
  • You want a headless agent SDK rather than a human-in-the-loop editor
  • You tend to accept green-looking multi-file diffs without running tests
  • You require a fully local traditional terminal with no account/cloud features
  • You cannot let command history, code context, outputs, or cloud-agent conversations leave the machine without strict controls
  • Credit-based AI usage and plan-seat changes would make developer costs hard to govern
  • Your team lacks review/rollback practices for commands and code changes suggested by agents
09Capabilities tracked
  • Tab completions
  • inline edits
  • Chat
  • Agent
  • MCPs
  • skills
  • hooks
  • rules
  • cloud agents
  • Bugbot
  • individual usage pools
  • Teams SSO/admin/analytics/privacy mode
  • Enterprise SCIM/audit/access controls/service accounts/AI code tracking API
  • Modern terminal
  • Terminal/Agent modes
  • Warp Agent
  • Claude Code/Codex/OpenCode/Gemini/Copilot orchestration
  • Oz agent/control plane
  • code editor
  • file tree
  • LSP
  • interactive code review
  • Warp Drive workflows/notebooks/prompts/plans/rules/env vars
  • Active AI + disable controls
  • Network Log
  • team code indexing
  • MCP integrations
  • agent profiles/guardrails
  • SSO/admin/roles/usage visibility
  • BYOLLM/AWS Bedrock
  • self-host cloud agents
  • SOC2 Type II/ZDR
10Failure modes · Documented, not buried
  • Agent edits can break tests/security despite clean diffs
  • Usage pools and on-demand billing are hard to forecast
  • Privacy Mode off can expose sensitive code context
  • Model/provider routing creates data and cost differences
  • MCP/cloud agents add permission and execution boundaries
  • Students may substitute AI edits for understanding
  • Agents can run risky commands
  • Terminal/repo/env-var context creates privacy boundaries
  • Credits, reloads, auto-reload, and seat limits can shift costs
  • BYOK/custom endpoints change retention policy
  • Enterprise self-host/BYOLLM/hybrid controls require contract and deployment review
  • Shared sessions/MCP integrations can leak sensitive context
  • Nontraditional UX may repel minimal-terminal users
11Evidence levelEditorial · hands-onEditorial · hands-on
12Sources verified · Receipts on the dossier
13Benchmark entries
  • Run 10 multi-file refactors and verify typecheck, tests, and security review.
    Pending.
  • Compare Auto/Composer/API usage pools on the same 20 coding tasks.
    Pending.
  • Compare requests with Privacy Mode on/off and review org enforcement.
    Pending.
  • Use one MCP server plus one cloud-agent automation on a sandbox repo.
    Pending.
  • Run 10 tasks: shell diagnosis, repo navigation, failing test fix, dependency issue, deployment command, rollback, refactor, log inspection, secrets-safe config, and unsafe-command refusal.
    Pending.
  • Compare Claude Code, Codex, OpenCode, Gemini CLI, and Warp Agent inside Warp.
    Pending.
  • Toggle Active AI, inspect cloud/session behavior, and verify ZDR/retention controls by plan.
    Pending.
14Alternatives tracked
  • GitHub Copilot
  • Windsurf
  • Cline
  • Zed
  • Factory
  • Ghostty
  • iTerm2
  • Cursor
  • Claude Code
  • GitHub Copilot CLI
  • OpenAI Codex CLI
15Pricing checked2026-06-072026-06-09
16Last verified2026-06-072026-06-09
16 metrics

Sixteen numbers, one shared midline.

CursorvsWarp

Both sit close together in the Build & code set; editorial fit is within four points. Cursor wins on value for money; Warp wins on source quality, privacy controls, and speed. For the canonical workflow, pick Cursor. Use Warp when its niche specifically wins above.

  1. Editorial fit
    Cursor81Warp84
  2. Source quality
    Cursor60Warp66
  3. Citation honesty
    Cursor58Warp58
  4. Privacy controls
    Cursor40Warp55
  5. Value for money
    Cursor72Warp58
  6. Speed
    Cursor50Warp78
  7. Integration
    Cursor72Warp82
  8. Onboarding
    Cursor50Warp78
  9. Reliability
    Cursor76Warp82
  10. Feature depth
    Cursor100Warp88
  11. Data portability
    Cursor55Warp73
  12. Transparency
    Cursor100Warp100
  13. Ecosystem reach
    Cursor72Warp82
  14. Documentation
    Cursor60Warp66
  15. Independence
    Cursor40Warp55
  16. Affordability
    Cursor55Warp55
Cursor · avg 65 · wins 2 of 160avg 73 · wins 11 of 16 · Warp
EvidenceCursor 0 · Warp 3
  1. 01Editorial fit
    81
    84
  2. 02Source quality
    60
    66
  3. 03Citation honesty
    58
    58
  4. 04Privacy controls
    40
    55
PrivacyCursor 1 · Warp 3
  1. 05Value for money
    72
    58
  2. 06Speed
    50
    78
  3. 07Integration
    72
    82
  4. 08Onboarding
    50
    78
CapabilityCursor 1 · Warp 2
  1. 09Reliability
    76
    82
  2. 10Feature depth
    100
    88
  3. 11Data portability
    55
    73
  4. 12Transparency
    100
    100
Cost & fitCursor 0 · Warp 3
  1. 13Ecosystem reach
    72
    82
  2. 14Documentation
    60
    66
  3. 15Independence
    40
    55
  4. 16Affordability
    55
    55
CARD A · Cursor
Build & code
Cursor
81/100
ROLEAI-native code editor and agentic refactor workspace
Editorial fit
81
Source quality
60
Citation honesty
58
Privacy controls
40
Value for money
72
Speed
50
FREEHobby
$20/MOPro
$60/MOPro+
FlagshipVerified 2026-06-07VP·METHOD

AI-native code editor and agentic refactor workspace — VS Code-compatible AI editor with Tab completion, Chat, Agent, MCPs, skills, hooks, cloud agents, Bugbot, Privacy Mode, and team/enterprise governance controls.

CARD B · Warp
Build & code
Warp
84/100
ROLEAI-native terminal and agentic development workspace
Editorial fit
84
Source quality
66
Citation honesty
58
Privacy controls
55
Value for money
58
Speed
78
CUSTOMFree
CUSTOMPro
CUSTOMEnterprise
SolidVerified 2026-06-09VP·METHOD

AI-native terminal and agentic development workspace — Agentic development environment born from a modern terminal, with Terminal and Agent modes, local/cloud coding agents, third-party CLI agent orchestration, Warp Drive workflows, code review, and enterprise privacy controls.

Privacy facets

Where each card is actually private.

CursorWarp
Training on your dataUnknownUnknown: Not statedPartialPartial: Opt-out available
EU data residencyNoNo: Not documentedPartialPartial: Enterprise tier only
SOC 2 attestationNoNo: Not documentedYesYes: Documented
Local-first by defaultNoNo: Cloud onlyNoNo: Cloud only
Capability split

What each card does uniquely.

Only Cursor13

  • Tab completions
  • inline edits
  • Chat
  • Agent
  • MCPs
  • skills
  • hooks
  • rules
  • cloud agents
  • Bugbot
  • individual usage pools
  • Teams SSO/admin/analytics/privacy mode
  • Enterprise SCIM/audit/access controls/service accounts/AI code tracking API

Shared0

No overlap detected.

Only Warp19

  • Modern terminal
  • Terminal/Agent modes
  • Warp Agent
  • Claude Code/Codex/OpenCode/Gemini/Copilot orchestration
  • Oz agent/control plane
  • code editor
  • file tree
  • LSP
  • interactive code review
  • Warp Drive workflows/notebooks/prompts/plans/rules/env vars
  • Active AI + disable controls
  • Network Log
  • team code indexing
  • MCP integrations
  • agent profiles/guardrails
  • SSO/admin/roles/usage visibility
  • BYOLLM/AWS Bedrock
  • self-host cloud agents
  • SOC2 Type II/ZDR
Failure modes

Where each card breaks.

Cursor

  • Agent edits can break tests/security despite clean diffs
  • Usage pools and on-demand billing are hard to forecast
  • Privacy Mode off can expose sensitive code context
  • Model/provider routing creates data and cost differences
  • MCP/cloud agents add permission and execution boundaries
  • Students may substitute AI edits for understanding

Warp

  • Agents can run risky commands
  • Terminal/repo/env-var context creates privacy boundaries
  • Credits, reloads, auto-reload, and seat limits can shift costs
  • BYOK/custom endpoints change retention policy
  • Enterprise self-host/BYOLLM/hybrid controls require contract and deployment review
  • Shared sessions/MCP integrations can leak sensitive context
  • Nontraditional UX may repel minimal-terminal users
Pricing

Pulled straight from each dossier.

Cursor

Build & code
  • FREEHobby
  • $20/MOPro
  • $60/MOPro+

raw · Hobby free · Individual Pro USD 20/mo, with Pro+/Ultra higher-capacity tiers · Teams Standard USD 40 monthly or USD 32 annual per seat · Teams Premium USD 120 monthly or USD 96 annual per seat · Enterprise custom · eligible students get one free Pro year.

Warp

Build & code
  • CUSTOMFree
  • CUSTOMPro
  • CUSTOMEnterprise

raw · Deepened 2026-06-08 from official Warp pricing/enterprise docs: Free $0 up to 10 seats with free AI credits, limited Agent/cloud-agent access, BYOK/custom endpoint support, any-harness-in-cloud beta, individual data controls, and limited Warp Drive/conversation storage. Build $20/mo or $18/mo annual with 1,500 credits, frontier OpenAI/Anthropic/Google models, reload credits with volume discounts, auto-reload, team spend cap, extended cloud agents, high indexing limits, unlimited Warp Drive/collaboration/storage, and private support. Max $200/$180 with 12× Build credits. Business $50/$45 up to 25 seats with team metrics, admin data controls, SAML SSO. Enterprise custom with unlimited seats, custom pools/usage terms, spend controls, Analytics API, BYOLLM, self-host cloud agents, custom indexing, cross-harness memory preview, onboarding, account manager, and shared Slack.

Verdict

Which card to actually pick.

Both sit close together in the Build & code set; editorial fit is within four points. Cursor wins on value for money; Warp wins on source quality, privacy controls, and speed. For the canonical workflow, pick Cursor. Use Warp when its niche specifically wins above.

Open Cursor's dossierOpen Warp's dossier
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