2018 Dodge Demon SRT vs 2024 Nissan Z Nismo
AI Telemetry Verdict:In this head-to-head, the 2018 Dodge Demon SRTholds the statistical edge in Performance Index (785). For the technical touge passes of Mount Fuji, the 2024 Nissan Z Nismois the superior technical chassis due to its refined lateral G-force profile.
2018 Dodge Demon SRT
Dodge
2024 Nissan Z Nismo
Nissan"The 2018 Dodge Demon SRT dominates the competition with superior Performance Index, making it the clear choice for all-around festival racing."
| 2018 Dodge Demon SRT | Metric | 2024 Nissan Z Nismo |
|---|---|---|
| 785 | Performance Index | 740 |
| 8.2 | Speed | 7.1 |
| 5.4 | Handling | 7.2 |
| 7.9 | Acceleration | 6.8 |
| 8.9 | Launch | 7 |
| 6.3 | Braking | 7.3 |
| 4 | Offroad | 3.5 |
| 203 | Top Speed (MPH) | 175 |
| 4280 | Weight (lbs) | 3704 |
| RWD | Drivetrain | RWD |
| 85,000 | Price (CR) | 65,000 |
📈 Technical Data Analysis:
Speed & Acceleration Analysis
When it comes to straight-line performance, the 2018 Dodge Demon SRT boasts a speed rating of 8.2, while the 2024 Nissan Z Nismo hits 7.1.
The 2018 Dodge Demon SRT has the edge in top-end velocity, reaching 203 MPH compared to the 2024 Nissan Z Nismo's 175 MPH.
Handling & Cornering Dynamics
In the tight technical sections of the Mount Fuji passes, handling is everything. The 2018 Dodge Demon SRT features a handling score of 5.4, whereas the 2024 Nissan Z Nismo manages 7.2.
The 2024 Nissan Z Nismo maintains superior stability through high-speed sweepers, minimizing the risk of traction loss.
Launch & Braking Efficiency
Off the line, the 2018 Dodge Demon SRT uses its 8.9 launch rating to grip and go, while the 2024 Nissan Z Nismo relies on its 7 rating.
Braking from high speeds is equally critical; the 2018 Dodge Demon SRT stops with a score of 6.3, while the 2024 Nissan Z Nismo records 7.3.
🏁 Race Scenario Breakdown
Higher top speed rating allows for sustained high-velocity overtaking.
Superior braking and handling allow for more aggressive entry and exit speeds.
Suspension travel and tire compound optimization for loose surfaces.