1992 Honda NSX-R vs 2016 Porsche Cayman GT4
AI Telemetry Verdict:In this head-to-head, the 2016 Porsche Cayman GT4holds the statistical edge in Performance Index (745). For the technical touge passes of Mount Fuji, the 2016 Porsche Cayman GT4is the superior technical chassis due to its refined lateral G-force profile.
1992 Honda NSX-R
Honda
2016 Porsche Cayman GT4
Porsche"The 2016 Porsche Cayman GT4 dominates the competition with superior Performance Index, making it the clear choice for all-around festival racing."
| 1992 Honda NSX-R | Metric | 2016 Porsche Cayman GT4 |
|---|---|---|
| 710 | Performance Index | 745 |
| 6.7 | Speed | 7 |
| 7.2 | Handling | 7.4 |
| 6.2 | Acceleration | 6.5 |
| 5.9 | Launch | 6.2 |
| 6.8 | Braking | 7.2 |
| 3.5 | Offroad | 3 |
| 168 | Top Speed (MPH) | 183 |
| 2712 | Weight (lbs) | 2955 |
| RWD | Drivetrain | RWD |
| 120,000 | Price (CR) | 85,000 |
📈 Technical Data Analysis:
Speed & Acceleration Analysis
When it comes to straight-line performance, the 1992 Honda NSX-R boasts a speed rating of 6.7, while the 2016 Porsche Cayman GT4 hits 7.
The 2016 Porsche Cayman GT4 pulls ahead in long stretches, making it a formidable opponent on the Tokyo highways.
Handling & Cornering Dynamics
In the tight technical sections of the Mount Fuji passes, handling is everything. The 1992 Honda NSX-R features a handling score of 7.2, whereas the 2016 Porsche Cayman GT4 manages 7.4.
The 2016 Porsche Cayman GT4 maintains superior stability through high-speed sweepers, minimizing the risk of traction loss.
Launch & Braking Efficiency
Off the line, the 1992 Honda NSX-R uses its 5.9 launch rating to grip and go, while the 2016 Porsche Cayman GT4 relies on its 6.2 rating.
Braking from high speeds is equally critical; the 1992 Honda NSX-R stops with a score of 6.8, while the 2016 Porsche Cayman GT4 records 7.2.
🏁 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.