Head to head / curated pair / cycle 04

Trae vs Cursor

Both products were given the identical 9 prompt vibeOps specification, 5 times each. Nothing on this page is an impression, all of it is a measurement from the same harness.

Trae logo
Trae

rank 30 / coding-agent

62.25

The cheapest paid plan in the index by a wide margin, and it is not a crippled tier: the free allowance completed most of a full run of the spec. Quality sits below the leading agents, mostly on the operational prompts, and the run to run spread is wider than the price suggests you should expect. Good value, not a leader.

Cursor logo
Cursor

rank 3 / coding-agent

78.65

The strongest edit loop we measured. It keeps a large working set in view, so the tenancy constraint from prompt 3 survived every later change without being restated. As a coding agent it produces no interface of its own, which caps the design subscore: what you get is exactly the quality of the framework and components you point it at. Everything it writes lands in your repository, so ownership is total.

Index gap

16.40

Cursor leads

Axes won

1 / 8

Trae versus Cursor, of ten axes

Faster median

Cursor

53.4 s per prompt

Higher pass rate

Cursor

86.7%

Every measurement, side by side

Cyan marks the better figure on each row. The delta column is the first product minus the second.

Trae compared with Cursor
MeasurementTraeCursorDelta
Composite index62.2578.65-16.40
Agent performance (weight 18)73.092.0-19.00
Reliability (weight 18)51.186.7-35.60
Scalability (weight 13)66.082.0-16.00
SEO and GEO (weight 12)54.058.0-4.00
API and MCP (weight 9)60.074.0-14.00
Integrations (weight 8)66.080.0-14.00
Design output (weight 7)66.066.0+0.00
Speed (weight 7)32.558.8-26.30
Value (weight 5)88.082.0+6.00
Code ownership (weight 3)96.099.0-3.00
Median seconds per prompt96.753.4+43.30
p10 seconds38.228.7+9.50
p90 seconds167.982.7+85.20
Executions failed133+10.00
HTML bytes, no JS18.0 KB24.0 KB-6144.00
LCP milliseconds1,9601,720+240.00
CLS0.0500.030+0.02
Entry price EUR3.0019.00-16.00

Screenshot diff

Both landing pages, captured by the lab on 14 Aug 2026 at 1440 by 900. Stored locally, never hotlinked.

Trae landing page, captured by the lab at 1440 by 900

Trae, captured 14 Aug 2026.

Cursor landing page, captured by the lab at 1440 by 900

Cursor, captured 14 Aug 2026.

Speed spread on a shared scale

Trae

38.2 / 96.7 / 167.9 seconds

Cursor

28.7 / 53.4 / 82.7 seconds

Axis by axis, who wins

Trae wins 1 of 10

  • Value88.0

Cursor wins 8 of 10

  • Agent performance92.0
  • Reliability86.7
  • Scalability82.0
  • SEO and GEO58.0
  • API and MCP74.0
  • Integrations80.0
  • Speed58.8
  • Code ownership99.0

Verdict

Cursor takes the composite by 16.40 points. It wins on the weighted total, but the axis table is where the real decision sits: Trae takes 1 axes and Cursor takes 8.

If the work in front of you is mostly interface, weight the design and speed rows. If it is a product with an API, webhooks and background jobs, weight agent performance, reliability and the API and MCP row, which together carry 45 of the 100 index points. If the project has to outlive its vendor, read the code ownership row first and treat everything else as secondary.

Both products in this comparison were measured in the same cycle, on the same specification, by the same harness. The per run data for each is on its product page and in /api/runs.json.

Other curated comparisons

Trae vs Cursor: measured comparison (2026) | LLM Tier