2020 Toyota GR Supra 3.0 vs 2024 Rivian R1S
AI Telemetry Verdict:In this head-to-head, the 2024 Rivian R1Sholds the statistical edge in Performance Index (765). For the technical touge passes of Mount Fuji, the 2020 Toyota GR Supra 3.0is the superior technical chassis due to its refined lateral G-force profile.

2020 Toyota GR Supra 3.0
Toyota
2024 Rivian R1S
Rivian"The 2024 Rivian R1S 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 Rivian R1S |
|---|---|---|
| 765 | Performance Index | 765 |
| 7.2 | Speed | 6 |
| 7 | Handling | 5.2 |
| 6.9 | Acceleration | 8.2 |
| 7.2 | Launch | 8.5 |
| 7.1 | Braking | 6 |
| 3.5 | Offroad | 8 |
| 165 | Top Speed (MPH) | 125 |
| 3400 | Weight (lbs) | 7000 |
| RWD | Drivetrain | AWD |
| 55,000 | Price (CR) | 84,000 |
📈 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 Rivian R1S hits 6.
The 2020 Toyota GR Supra 3.0 has the edge in top-end velocity, reaching 165 MPH compared to the 2024 Rivian R1S's 125 MPH.
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 Rivian R1S manages 5.2.
The 2020 Toyota GR Supra 3.0 offers surgical precision in corners, allowing for later braking and earlier power application.
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 Rivian R1S relies on its 8.5 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 Rivian R1S records 6.
🏁 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.