Tensor core performance of NVIDIA Tesla P4
Jawaban
The short answer: NVIDIA Tesla P4 runs at FP16 TFLOPS with 192 GB/s of memory bandwidth. The longer answer depends on what you run.
For dense FP16 training with large batches, NVIDIA Tesla P4 saturates tensor cores and delivers throughput close to peak FLOPS. For memory-bound serving on long-context foundation models, bandwidth dominates — the 192 GB/s figure matters more than headline TFLOPS. For scientific computing, FP32 at 5.5 TFLOPS is the relevant number and puts NVIDIA Tesla P4 in line with the HPC expectations of its Pascal class.
Get NVIDIA Tesla P4 on Cherry Servers starting at $0.16/hr — live pricing and fast provisioning.
Lebih Banyak FAQ tentang NVIDIA Tesla P4
Ulasan Penyedia GPU Cherry Servers & Fakta Utama (April 2026)
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Server GPU bare metal dengan 24 tahun pengalaman hosting dan kontrol penuh tingkat perangkat keras.
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| Ikhtisar | |
| Peringkat Trustpilot | 4.6 |
| Kantor Pusat | Lithuania |
| Jenis Penyedia | Tidak tersedia |
| Terbaik Untuk | Pelatihan AI inferensi fine-tuning rendering riset HPC AI generatif pembelajaran mendalam |
| Perangkat Keras GPU | |
| Model GPU | A100 A40 A16 A10 A2 Tesla P4 |
| Maks VRAM (GB) | 80 |
| Maks GPU/Instance | 2 |
| Interkoneksi | PCIe |
| Harga | |
| Harga Mulai ($/jam) | $0.16/hr |
| Granularitas Penagihan | Per jam |
| Spot/Preemptible | Tidak |
| Diskon Cadangan | Tidak tersedia |
| Kredit Gratis | Tidak ada |
| Biaya Keluar | Tidak tersedia |
| Penyimpanan | NVMe SSD, Elastic Block Storage ($0.071/GB/bln) |
| Infrastruktur | |
| Wilayah | Lithuania, Belanda, Jerman, Swedia, AS, Singapura (6 lokasi) |
| SLA Waktu Aktif | 99,97% |
| Pengalaman Pengembang | |
| Kerangka Kerja | PyTorch TensorFlow CUDA (bare metal — kontrol tumpukan penuh) |
| Dukungan Docker | Ya |
| Akses SSH | Ya |
| Jupyter Notebooks | Tidak |
| API / CLI | Ya |
| Waktu Setup | Menit |
| Dukungan Kubernetes | Ya |
| Ketentuan Bisnis | |
| Komitmen Minimum | Tidak ada |
| Kepatuhan | ISO 27001 ISO 20000-1 GDPR PCI DSS |
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