NVIDIA L40sVSNVIDIA H100
AI基准测试对决 2026
NVIDIA L40s
Ada Lovelace48GB
$8,000-10000
企业级
Professional
NVIDIA H100
Hopper80GB
$25,000-30000
企业级
Data Center
不同并发级别
NVIDIA H100在128并发请求下测试（数据中心负载），而NVIDIA L40s在16并发请求下测试（典型工作站负载）。高并发显示吞吐量能力，但可能不反映单用户延迟。
LLM Inference
| 模型 | NVIDIA L40s | NVIDIA H100 | 胜者 |
|---|---|---|---|
Typhoon2.5-Qwen3-4B越高越好 | 1,523tok/s | 9,931tok/s | NVIDIA H100 |
GPT-OSS-20B越高越好 | 910tok/s | 8,553tok/s | NVIDIA H100 |
Qwen3-4B-Instruct-FP8越高越好 | N/A | N/A | N/A |
Vision-Language
| 模型 | NVIDIA L40s | NVIDIA H100 | 胜者 |
|---|---|---|---|
Qwen3-VL-4B越高越好 | 1,050tok/s | 7,790tok/s | NVIDIA H100 |
Qwen3-VL-8B越高越好 | 746tok/s | 7,035tok/s | NVIDIA H100 |
Typhoon-OCR-3B越高越好 | 2,419tok/s | 14,019tok/s | NVIDIA H100 |
Image Generation
| 模型 | NVIDIA L40s | NVIDIA H100 | 胜者 |
|---|---|---|---|
Qwen-Image越低越好 | 102.00sec | 28.00sec | NVIDIA H100 |
Qwen-Image-Edit越低越好 | 104.00sec | 29.00sec | NVIDIA H100 |
Video Generation
| 模型 | NVIDIA L40s | NVIDIA H100 | 胜者 |
|---|---|---|---|
Wan2.2-5B越低越好 | 412.00sec | 180.00sec | NVIDIA H100 |
Wan2.2-14B越低越好 | 940.00sec | 404.00sec | NVIDIA H100 |
Speech-to-Text
| 模型 | NVIDIA L40s | NVIDIA H100 | 胜者 |
|---|---|---|---|
Typhoon-ASR越高越好 | 0.364xx realtime | 0.392xx realtime | NVIDIA H100 |
赢家分析
深入了解每款GPU基于技术规格的性能差异原因
技术分析摘要
NVIDIA H100 wins 10 out of 10 benchmarks, excelling in LLM Inference and Vision-Language. Its HBM3 memory bandwidth provides a decisive advantage for AI inference workloads.
主要差异
- NVIDIA L40s uses Ada Lovelace architecture while NVIDIA H100 uses Hopper
- NVIDIA H100's HBM3 memory provides exceptional bandwidth for AI workloads
LLM Inference
NVIDIA H100 wins in LLM inference because NVIDIA H100's superior memory bandwidth (3.4TB/s vs 864GB/s) enables faster token generation, and HBM3 memory provides exceptional bandwidth for memory-bound LLM operations.
Vision-Language
NVIDIA H100 excels at vision-language tasks due to higher memory bandwidth accelerates image token processing, and more VRAM (80GB) handles larger image batches efficiently.
Image Generation
NVIDIA H100 leads in image generation because faster memory enables quicker diffusion iterations, and Hopper architecture optimizations accelerate denoising operations.
Video Generation
NVIDIA H100 dominates video generation with significantly more VRAM (80GB) maintains temporal coherence across frames, and 3.4TB/s bandwidth handles high-throughput video data.
Speech-to-Text
NVIDIA H100 excels at speech-to-text because superior memory bandwidth enables faster audio feature processing, and 4th Gen Tensor Cores accelerate attention-based speech recognition.
技术规格
NVIDIA L40s
NVIDIA H100
总体胜者
NVIDIA H100
10 胜出 10 benchmarks
0
NVIDIA L40s
10
NVIDIA H100
NVIDIA L40s 优势
- -
NVIDIA H100 优势
- More VRAM (80GB vs 48GB)
- Strong in LLM Inference
- Dominates in Vision-Language
- Dominates in Image Generation
Frequently Asked Questions
NVIDIA H100 outperforms NVIDIA L40s in 10 out of 10 AI benchmarks. The NVIDIA H100's Hopper architecture features the Transformer Engine with FP8 precision, specifically designed for large language models and transformer-based AI workloads. With 3.4 TB/s memory bandwidth and 80GB HBM3 memory, it delivers superior throughput for AI inference workloads.
NVIDIA L40s has 48GB of GDDR6 memory with 864 GB/s bandwidth. NVIDIA H100 has 80GB of HBM3 memory with 3.4 TB/s bandwidth. NVIDIA H100's HBM3 memory provides exceptional bandwidth for memory-bound AI workloads like LLM inference.
NVIDIA H100 is faster for LLM inference. LLM performance is heavily dependent on memory bandwidth - NVIDIA H100's 3.4 TB/s HBM3 enables faster token generation compared to NVIDIA L40s's 864 GB/s.
NVIDIA L40s has a TDP of 350W while NVIDIA H100 has a TDP of 700W. NVIDIA L40s is more power efficient, making it suitable for deployments with power constraints. For cloud deployments, consider Float16.cloud where you can access these GPUs without managing power infrastructure.
NVIDIA L40s is priced around $8,000-10000 (enterprise/datacenter), while NVIDIA H100 costs approximately $25,000-30000 (enterprise/datacenter).