GPU Benchmark Test

A GPU benchmark test measures how your graphics processor handles defined rendering and compute workloads. For capability assessment, the goal is not a leaderboard rank but an answer: can this GPU sustain what you need at your settings?

Our browser-based test uses WebGL2 (with WebGL1 fallback) to validate graphics pipeline health, stability under duration, and headroom before you rely on native games, AI frameworks, or creative applications.

The benchmark tool lives on the run page at /run/. It executes client-side WebGL stress workloads, detects GPU renderer info, scores capability and stability, analyzes workload pressure by scene complexity, and exports JSON performance reports.

Adjust render intensity (1 to 40), duration, scene complexity, and API mode. Live telemetry updates throughout the session. All processing stays in your browser with no automatic upload.

Limitation detection finds the binding constraint: VRAM capacity, memory bandwidth, thermal throttling, power delivery, or CPU pairing. Effective performance equals the minimum of these caps.

Run sustained high-intensity sessions and watch stability plus minimum FPS. Gradual decline often signals thermal or power limits; stutter at high texture settings often signals VRAM limits.

• Hardware bottlenecks in the graphics pipeline
• VRAM limitations for high-resolution assets
• Bandwidth limitations under heavy streaming
• Thermal limitations on laptops and compact PCs
• Power limitations on battery or weak PSUs

Modern workloads stack ray tracing, upscaling, frame generation, complex shaders, and high-resolution textures. Each feature multiplies GPU cost on top of base resolution.

Test features incrementally in native apps. Browser complex scenes approximate shader pressure; ray tracing and frame generation require title-specific validation.

• Ray tracing performance in supported titles
• Upscaling technologies (DLSS, FSR, XeSS)
• Frame generation and latency tradeoffs
• Shader performance under heavy materials
• Texture rendering and memory footprint

Longevity analysis estimates remaining useful life as software requirements rise. Track performance headroom against expected growth in game specs, AI model sizes, and creative project complexity.

Performance aging from thermals, driver abandonment, and missing features can shorten lifecycle independent of day-one FPS.

• Future game readiness at target settings
• Software requirement trend tracking
• Performance aging and stability drift
• Upgrade timing based on headroom decay
• Hardware lifecycle for cost planning

Upgrade when validated data shows binding GPU limits block primary workloads and productivity gains justify total cost including PSU, platform, and downtime.

Remaining useful life, performance headroom, upcoming software demands, and cost-benefit analysis together answer when to replace hardware instead of lowering settings again.

• Remaining useful life assessment
• Performance headroom vs requirements
• Upcoming software and feature demands
• Cost-benefit and ROI evaluation
• Replacement planning and compatibility checks