GPU Performance Calculator Form
Enter hardware values, choose a workload profile, then calculate performance. Results appear above this form after submission.
Example Data Table
| Profile | Shader Cores | Boost MHz | Tensor Cores | Memory Bus | Memory Gbps | TDP W | Likely Use |
|---|---|---|---|---|---|---|---|
| Compact Analysis GPU | 4096 | 1950 | 128 | 192 | 16 | 180 | Light FEA, CAD, and viewport work |
| Balanced Workstation GPU | 7680 | 2250 | 240 | 256 | 20 | 285 | General engineering, rendering, and AI support |
| Throughput Compute GPU | 16384 | 2100 | 512 | 512 | 24 | 450 | Large simulation, training, and dense compute jobs |
Formula Used
1) Theoretical FP32 Throughput
TFLOPS = Shader Cores × FP32 Ops/Cycle × Boost Clock (GHz) ÷ 1000
2) Theoretical Tensor Throughput
Tensor TFLOPS = Tensor Cores × Tensor Ops/Cycle × Boost Clock (GHz) ÷ 1000
3) Memory Bandwidth
GB/s = (Memory Bus Width in bits ÷ 8) × Memory Speed in Gbps
4) Sustained FP32 Throughput
Sustained TFLOPS = Theoretical FP32 TFLOPS × Utilization × Efficiency
5) Performance per Watt
TFLOPS/W = Sustained FP32 TFLOPS ÷ Board Power
6) Compute-to-Memory Balance
Ratio = Sustained FP32 TFLOPS ÷ Memory Bandwidth GB/s
The final engineering score uses weighted sub-scores for compute, tensor capability, memory, efficiency, cache, RT capability, and workload balance. The weighting changes with the workload profile you select.
How to Use This Calculator
- Enter a GPU name so the report is easier to identify later.
- Choose the workload profile that best matches your engineering task.
- Provide shader, tensor, and RT core counts from your specification sheet.
- Fill in base clock, boost clock, memory bus width, and memory speed.
- Add L2 cache size, board power, utilization, and estimated efficiency.
- Click the calculate button to show results above the form.
- Review throughput, bandwidth, efficiency, and balance before deciding fit.
- Export the report as CSV or PDF for documentation.
Frequently Asked Questions
1) What does this calculator estimate?
This calculator estimates theoretical compute throughput, sustained throughput, tensor performance, memory bandwidth, performance per watt, and an engineering-focused composite score for a chosen workload profile.
2) Why are there theoretical and sustained values?
Theoretical values assume ideal peak behavior. Sustained values apply utilization and efficiency inputs, giving a more realistic planning estimate for thermal limits, software overhead, and imperfect scaling.
3) Why is boost clock used in the main throughput formula?
Boost clock is commonly used for headline peak calculations because vendors publish performance near peak dynamic frequency. Sustained values then reduce that peak with your utilization and efficiency assumptions.
4) Is the tensor estimate a real benchmark result?
No. It is a structured estimate based on your tensor core count, tensor operations per cycle, and clock rate. Real software, data type, and kernel choice can change actual results significantly.
5) What does the balance score mean?
The balance score compares sustained compute against memory bandwidth for the selected workload. A weak score suggests either memory pressure or underutilized compute resources may reduce practical performance.
6) Can this replace real benchmarks?
No. It is a planning and sizing tool. Benchmarks remain essential because drivers, kernels, cooling, memory behavior, and application design all affect delivered performance in real projects.
7) Why is cache included in the score?
Cache can reduce memory traffic and improve locality, especially for repeated accesses. It does not directly create FLOPS, but it can improve overall behavior in many engineering workloads.
8) How can I improve a weak overall score?
Match the workload profile carefully, raise sustained efficiency with better cooling, increase memory bandwidth, reduce memory bottlenecks, or choose a GPU with stronger compute, tensor, or RT resources.