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Training Time Estimator
Estimate duration & cost · Compare single / multi-GPU scaling
Configuration
Model presets
ResNet-50
BERT-base
GPT-2 (124M)
LLaMA-7B
Stable Diffusion
Dataset size (samples)
Model parameters (millions)
GPU type
H100 SXM (312 TFLOPS FP16), $32.5/hr
A100 80GB (197 TFLOPS), $22.8/hr
A100 40GB (156 TFLOPS), $18.2/hr
A6000 (83 TFLOPS), $13.5/hr
A5000 (71 TFLOPS), $10.2/hr
RTX 4090 (65 TFLOPS), $8.9/hr
RTX 4080 (51 TFLOPS), $6.5/hr
RTX 4070 Ti (40 TFLOPS), $5.2/hr
RTX 3090 (35 TFLOPS), $4.1/hr
RTX 3080 (28 TFLOPS), $3.2/hr
RTX 3070 (21 TFLOPS), $2.5/hr
RTX 3060 (16 TFLOPS), $1.9/hr
T4 (12 TFLOPS), $1.2/hr
V100 (8 TFLOPS), $0.9/hr
P100 (6 TFLOPS), $0.6/hr
K80 (4.5 TFLOPS), $0.45/hr
Batch size
Epochs
Precision
FP32 (1x)
FP16 (2x throughput)
BF16 (2x throughput)
INT8 (4x throughput)
Calculate
Results & multi‑GPU comparison
Time per step
,
Steps per epoch
,
Total training time
,
Estimated cost (single GPU)
,
Multi‑GPU scaling (estimated)
1 GPU
,
,
2 GPUs
,
,
4 GPUs
,
,
8 GPUs
,
,
Scaling efficiency:
based on workload
* TFLOPS based on advertised mixed‑precision. Cloud rates approximate (on‑demand). Scaling efficiency assumes 0.85/0.75/0.65 for 2/4/8 GPUs.