Tesla Cybertruck with Cyberquad ATV is a detailed Vehicles asset built for professional 3D pipelines, available at $189. You are getting 263,043 polygons and 278,544 vertices, measured rather than estimated. Treat the figure as a planning number: it behaves one way in a single render and another in a level with fifty instances.
The texture set counts 23 maps, delivered at 4096 x 4096. It is a StemCell model, so it ships in TurboSquid's multi-format standard with PBR materials that carry over between renderers instead of needing to be rebuilt per engine. Objects sit at the origin with clean transforms, so duplicating the asset across an environment costs nothing extra.
On this listing the stated applications are driving simulation, game traffic and film & TV VFX. The listing dates back to 2020, and it remains one of the models we keep current. Common uses are film and TV backgrounds, game traffic and architectural visualization.
Questions About This Model
What is the Tesla Cybertruck with Cyberquad ATV model typically used for?
The listing names driving simulation, game traffic and film & TV VFX as the main applications. In practice it also works anywhere a finished vehicles object is needed without modeling it from scratch.
Which industries use the Tesla Cybertruck with Cyberquad ATV model?
Simulation, Game Development, Film & Video Production and Architecture are the primary industries on this listing. The license, however, is Editorial Uses Only: the model depicts a real branded product, so it may appear in editorial work in those fields, but not in advertising or in products for sale.
Where can I buy the Tesla Cybertruck with Cyberquad ATV 3D model?
It is sold through TurboSquid, where this listing has been available since 2020. Purchase, download and licensing are handled by TurboSquid; delivery is immediate after checkout.
What does StemCell mean for the Tesla Cybertruck with Cyberquad ATV model?
StemCell covers both geometry and shading: the model is delivered across formats with materials that stay equivalent instead of needing per-engine conversion.
