2020 Toyota GR Supra 3.0 vs 2024 Alpine A110 R
AI Telemetry Verdict:In this head-to-head, the 2024 Alpine A110 Rholds the statistical edge in Performance Index (788). For the technical touge passes of Mount Fuji, the 2024 Alpine A110 Ris the superior technical chassis due to its refined lateral G-force profile.
2020 Toyota GR Supra 3.0
Toyota
2024 Alpine A110 R
Alpine"The 2024 Alpine A110 R dominates the competition with superior Performance Index, making it the clear choice for all-around festival racing."
| 2020 Toyota GR Supra 3.0 | Metric | 2024 Alpine A110 R |
|---|---|---|
| 765 | Performance Index | 788 |
| 7.2 | Speed | 7.2 |
| 7 | Handling | 8.2 |
| 6.9 | Acceleration | 7.1 |
| 7.2 | Launch | 7.4 |
| 7.1 | Braking | 8.3 |
| 3.5 | Offroad | 3 |
| 165 | Top Speed (MPH) | 177 |
| 3400 | Weight (lbs) | 2385 |
| RWD | Drivetrain | RWD |
| 55,000 | Price (CR) | 110,000 |
📈 Technical Data Analysis:
Speed & Acceleration Analysis
When it comes to straight-line performance, the 2020 Toyota GR Supra 3.0 boasts a speed rating of 7.2, while the 2024 Alpine A110 R hits 7.2.
The 2024 Alpine A110 R 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 2020 Toyota GR Supra 3.0 features a handling score of 7, whereas the 2024 Alpine A110 R manages 8.2.
The 2024 Alpine A110 R maintains superior stability through high-speed sweepers, minimizing the risk of traction loss.
Launch & Braking Efficiency
Off the line, the 2020 Toyota GR Supra 3.0 uses its 7.2 launch rating to grip and go, while the 2024 Alpine A110 R relies on its 7.4 rating.
Braking from high speeds is equally critical; the 2020 Toyota GR Supra 3.0 stops with a score of 7.1, while the 2024 Alpine A110 R records 8.3.
🏁 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.