NVIDIA L2 (Entry-Level Ada Inference)
Overview
NVIDIA L2 is the entry-level inference card in the Ada Lovelace lineup, positioned below the L4. With 24GB GDDR6 memory and a TDP of just 50-75W, it fits in a single PCIe slot.
Targeted at edge servers, telecom operators, retail, and other scenarios requiring low-power AI inference.
Core Specifications
| Item | Spec |
|---|---|
| Architecture | Ada Lovelace (AD102 cut-down) |
| Process | TSMC 4N |
| CUDA Cores | 4,608 |
| Tensor Cores | 144 (4th Gen) |
| RT Cores | 36 (3rd Gen) |
| Memory | 24 GB GDDR6 |
| Memory Bandwidth | 384 GB/s (16 Gbps × 192-bit) |
| FP8 Tensor | 96 TFLOPS (sparse) / 48 TFLOPS (dense) |
| INT8 Tensor | 96 TOPS (dense) / 192 TOPS (sparse) |
| TDP | 50-75 W |
| Form Factor | PCIe Gen4 ×16 single-slot / half-height half-length |
| Launch | 2024-Q4 |
| Price | $1,500-$2,000 |
L2 vs L4 vs T4 Comparison
| Metric | L2 | L4 | T4 |
|---|---|---|---|
| Architecture | Ada | Ada | Turing |
| CUDA Cores | 4,608 | 7,680 | 2,560 |
| Memory | 24GB GDDR6 | 24GB GDDR6 | 16GB GDDR6 |
| Bandwidth | 384 GB/s | 300 GB/s | 320 GB/s |
| FP8 Tensor (sparse) | 96 TFLOPS | 485 TFLOPS | N/A |
| TDP | 50-75W | 72W | 70W |
| Form Factor | Single-slot | Single-slot | Single-slot |
The L2's FP8 performance is about 20% of the L4 (96/485 sparse), but with a similar TDP → the L4 offers better performance-per-watt.
Use Cases
- ✅ Edge server AI inference (5G MEC)
- ✅ Telecom vRAN + AI convergence
- ✅ Retail edge AI (video analytics)
- ✅ Embedded data centers
- ❌ Large model inference (use L40S/H100)
- ❌ Training (lacks FP8 compute advantage)
Vendor Information
| Item | Detail |
|---|---|
| Vendor | NVIDIA |
| Target Market | Edge servers, telecom, retail |
| Price | $1,500-$2,000 |
Related Cards
- NVIDIA L4 - Same-gen flagship
- NVIDIA L40S - Data center version
- NVIDIA T4 - Previous-gen entry-level
- Qualcomm Cloud AI 100 - Comparable low-power ASIC