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The GPU That Runs 80% of Enterprise AI Inference — And Nobody Talks About It
The H100 gets the keynotes. The L40S gets the data center. The T4 gets the actual work done — quietly, efficiently, and at a price point that makes GPU-accelerated inference viable for edge servers, VDI deployments, and branch office AI. 와 함께 16 GB GDDR6, 70승 TDP, and a low-profile PCIe form factor, the NVIDIA Tesla T4 fits in 1U servers that cannot physically accommodate a dual-slot 300W GPU. It is the inference GPU for the other 80% of your data center — the servers that run in edge POPs, remote offices, and colocation racks where every watt counts.
기술 사양
| 매개변수 | 사양 |
|---|---|
| GPU Architecture | NVIDIA Turing (TU104-895-A1) |
| CUDA Cores | 2,560 |
| Tensor Cores | 320 (2nd Gen) |
| 메모리 | 16 GB GDDR6 (no ECC on Tesla T4) |
| Memory Bandwidth | 320 GB/초 (256-조금) |
| 인터페이스 | PCIe 3.0 x16 |
| FP32 Performance | 8.1 TFLOPS |
| FP16 Performance | 65 TFLOPS (Tensor Core) |
| INT8 Performance | 130 TOPS |
| INT4 Performance | 260 TOPS |
| TDP | 70승 (passive cooling — requires chassis airflow) |
| 폼 팩터 | Single-slot, 저 프로파일 (LP), half-length PCIe |
| Power Connector | None — powered entirely through PCIe slot (70W max via PCIe 3.0 x16) |
| NVLink | 지원되지 않습니다 |
| MIG | 지원되지 않습니다 |
| vGPU Support | Yes — NVIDIA vWS, vPC, vApps for virtual desktops |
| 물리적 크기 | 168 엑스 69 mm (single-slot low-profile) |
| 작동 온도 | 0° C ~ 45 ° C (passive — server fans provide cooling) |
| Compatible Servers | 델 R470, R660, R670, R760, R770, xFusion 1288H/2288H V7 (any server with PCIe 3.0 x16 and adequate airflow) |
| 보증 | 3-년도 (manufacturer) |
T4 vs L40S vs A2 — The Inference GPU Showdown
| 특징 | T4 16GB | L40S 48GB | A2 16GB |
|---|---|---|---|
| CUDA Cores | 2,560 | 18,176 | 1,280 |
| 메모리 | 16 GB GDDR6 | 48 GB GDDR6 ECC | 16 GB GDDR6 ECC |
| TDP | 70승 (passive) | 300승 (active) | 60승 (passive) |
| 폼 팩터 | Single-slot LP | Dual-slot FHFL | Single-slot HHHL |
| Inference Throughput (ResNet-50) | ~4,000 images/s | ~16,000 images/s | ~2,000 images/s |
| Best for | Edge inference, VDI, video transcoding, small model serving | Data center inference, 13B+ LLM serving | Entry-level VDI, light inference |
| 가격 (relative to L40S) | ~15% | 100% | ~10% |
Where the T4 Excels
- Edge AI: A 70W GPU in a 1U server at a retail store running real-time object detection on 16 camera feeds. No supplemental power cable, no chassis modification, no thermal recalc. The T4 is the only inference GPU that fits in most 1U servers without a GPU enablement kit.
- VDI with NVIDIA vGPU: 16 GB supports 4-8 concurrent virtual desktop users with GPU acceleration for CAD, GIS, and medical imaging. Deploy 4x T4 in a Dell R760 and support 32 concurrent GPU-accelerated VDI users on one 2U server.
- Video Transcoding: The T4 includes a dedicated NVENC/NVDEC engine that transcodes up to 38 simultaneous 1080p30 video streams. For live streaming platforms, video conferencing backends, and surveillance analytics, the T4’s media engine is more important than its CUDA core count.
- Small Model Inference Serving: BERT, ResNet, YOLO, Whisper — models under 2B parameters fit comfortably in 16 GB at FP16 precision. A single T4 can serve these models to hundreds of concurrent API requests without breaking 70W.
Source Through Xincuan
We supply T4 GPUs pre-installed in Dell and xFusion servers, or as retrofit kits for existing platforms. Factory-direct pricing, 3-1년 보증, global shipping.
