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L40S vs A100 vs RTX 6000 Ада：一张表看懂推理卡定位

AI 推理时代的 GPU 选型比训练时代复杂：训练看总量，推理看性价比和部署密度。NVIDIA L40S 恰好卡在 A100 与 RTX 6000 Ada 之间的甜区：

Атрибут	NVIDIA L40S	NVIDIA A100 80 ГБ	RTX 6000 Ада
Architecture	Ada Lovelace	Ampere	Ada Lovelace
Память	48 ГБ GDDR6 ECC	80 ГБ HBM2e	48 ГБ GDDR6 ECC
Memory bandwidth	864 ГБ/с	2,039 ГБ/с	960 ГБ/с
FP16 (Tensor)	733 терафлопс	312 терафлопс	~1,198 TFLOPS (FP16)*
РП8 (Tensor)	1,466 терафлопс	—	~2,396 TFLOPS*
Max power	350 Вт	400 Вт	300 Вт
Primary role	Inference + рендеринг	Обучение (legacy)	Workstation graphics

*RTX 6000 Ada Tensor figures per NVIDIA spec sheet; the practical takeaway is that L40S delivers data-center-class inference and graphics in one PCIe card at a power envelope any 2U server can feed.

Core Specifications

Атрибут	Спецификация
Architecture	NVIDIA Ada Lovelace
GPU memory	48 GB GDDR6 with ECC
Memory bandwidth	864 ГБ/с
CUDA / RT / Tensor cores	18,176 / 142 / 568
Tensor performance	РП8: 1,466 терафлопс; FP16: 733 терафлопс; TF32: 366 терафлопс
RT core performance	212 терафлопс
Interconnect	PCIe Gen4 x16 (64 GB/s bidirectional)
Max power	350 Вт (passive, data center cooling)
Фактор формы	Dual-slot PCIe accelerator
Software stack	CUDA, TensorRT / TRT-LLM, NVIDIA AI Enterprise, vGPU

NVIDIA L40S 48GB AI GPU — NVIDIA L40S: Ada Lovelace inference and graphics accelerator in a dual-slot PCIe form factor.

Why 2026 Inference Deployments Pick the L40S

Three numbers drive the decision: 1,466 TFLOPS of FP8 for quantized inference (INT8/FP8 is where production LLM serving lives), 350 Вт power draw that fits the air-cooled racks most enterprises already run, и PCIe Gen4 x16 compatibility that drops into existing server slots without an NVLink-scale chassis. Paired with TensorRT-LLM and vLLM, a single L40S serves production LLM and RAG workloads at a per-token cost well below H100-class hardware — which is why it became the default inference accelerator for on-prem deployments.

Graphics and Rendering: The Second Half of the Story

L40S is also a full graphics card: 212 TFLOPS of RT core performance covers CAD, product visualization and Omniverse/NeRF workloads, so one GPU tier serves both the inference cluster and the rendering farm. That dual role is rare at this price point — it collapses two hardware budgets into one SKU.

Deployment in Standard Servers

Власть: 350 W per card — two cards fit a 2U node’s PSU budget (см. PowerEdge R760, 2 Икс 350 W double-width GPU support, or the xFusion 2288H V7 с 4 x double-width slots).
PCIe: Gen4 x16 card runs in Gen5 slots at full Gen4 bandwidth — no platform mismatch on 2026 серверы.
Охлаждение: Passive heatsink, data center airflow required — plan server airflow direction before racking.
Сеть: for multi-GPU inference, pair with a 100GbE NIC (E810-CQDA2) to feed model shards without host-CPU bottlenecks.
Программное обеспечение: vGPU licensing extends the card to VDI graphics pools; TRT-LLM profiles cover the major open models.

NVIDIA L40S product photo — L40S dual-slot passive design: drop-in for standard PCIe Gen4/Gen5 server slots.

Часто задаваемые вопросы о покупке

Training or inference? L40S is inference- and graphics-optimized; training-heavy fleets should look at H200-class (see our AI hardware insights).
ЕСС? Да — 48GB GDDR6 with ECC for data integrity.
НВЛинк? The L40S is a PCIe-scale card; multi-card scaling is via software (vLLM/TensorRT) and network, not NVLink mesh.
Which servers? Any Gen4/Gen5 PCIe x16 slot with 350W power delivery — 760 рэндов, 2288H V7 and similar.
Гарантия? Served with our standard hardware warranty; contact us for volume pricing.

NVIDIA L40S data center GPU — Board partner variants (shown: PNY) carry the same NVIDIA spec and driver stack.

Building an on-prem inference tier? We configure L40S-ready nodes with power/cooling matched builds and 100GbE fabric — factory-direct pricing, 3-год гарантии, global shipping and free AI-hardware consultation from our authorized partner team. Contact us for an inference TCO comparison.