A load test is a date on the calendar. A coding agent is excellent at the change in front of it. Both can be excellent for that hour. Then the calendar goes quiet, and the next failure starts from zero.
DeepXplore is what you leave running. The test stays available all year. A failure turns into a cause, then a pull request, on a runner that brings the same skills and the same view every time.
PerformanceLoad tools generate traffic.
Load tools win the flood of users from many regions. DeepXplore wins once the test has to stay up, look like production, and lead to a fix: the long run, the journeys, the data, the cause, and running the test again.
| Performance | Load tools | DeepXplore |
|---|---|---|
| Scale | Multi-region load | Realistic traffic. Not built to win on raw megascale |
| A long run | Metered by virtual users, hours, or plan | Runs 24/7. Traffic is included in the plan |
| Journeys | Scripts and plugins | Detects the test cases, including authentication |
| Test data | You bring the data | GDPR-compliant synthetic data |
| After the report | What failed under load | An anomaly and a ranked cause |
| The fix | The job ends at the report | Runs the test again once the fix is in |
Green wins the row. Yellow is partial. Red is not that product’s job.
The spec already describes the journeys. Each step can hand its data to the next, and the load can rise and fall the way a real day does.
OpenAPI in. Journeys out, including authentication.
Coding agentsThe organization is already mapped.
Coding agents win the editor and the terminal. DeepXplore wins with isolated shared runners for the organization: skills and rules kept up to date, the graph, the guardrails, what can start it, and the range of models.
| Coding | Coding agents | DeepXplore |
|---|---|---|
| Where you work | Editor and terminal | Isolated shared runners for the organization |
| Shared context | Skills and rules per person or environment | Detects skills and rules, and keeps them up to date with every change in your organization |
| Guardrails | Cloud runs can be isolated | Permissions sit outside the model, the same every run |
| What it knows | The repositories you connect | A graph built from knowledge, change, and telemetry |
| What starts the run | A prompt, Slack, or a ticket | A performance test, an external alert, a prompt, or a ticket |
| Model | Their model, or a narrower list | A wide range of providers and models |
Green wins the row. Yellow is partial. Red is not that product’s job.
The cause is already in the telemetry and in what just changed. A shared runner can pick that up without borrowing someone’s laptop.
Ranked cause from telemetry and change.
PricingOne bill instead of two.
A team that wants both jobs today buys them apart: a load plan, plus a seat for each person who codes. This example is five people, tests available all year, list prices on 29 September 2026, USD, excluding VAT.
Bought separately
- OctoPerf Unlimited, the published plan for ongoing runs: from $999
- Cursor Teams: $40 × 5 people = $200
- Model usage above each plan’s included amount is extra
DeepXplore only
- Pro: performance tests, Root Cause Analysis and DeepXplore Code on one plan
- Generated traffic included. $15 of AI spend included
- AI above $15 is billed at model rates, as on the other tools
What you keep
- $1,199 − $149 on these list prices
- About $12,600 over a year, before extra AI usage
- Swap Cursor for Claude Pro ($20 × 5) and you still keep about $950 a month
Bought apart, the load test ends as a report. Someone then opens a second product, pastes the failure into a chat, and starts the fix from a screenshot of a run they never watched. Switch to DeepXplore Pro and that handoff is gone. The test, the root cause, and the code stay on one plan. When the change lands, the same tests run again and say whether it held.
OctoPerf · Cursor · Claude Pro