📄 中文摘要
H100 是一款优秀的 GPU，但对于许多工作负载而言，4090 或 A100 就足够了。许多团队选择 H100 是因为它看起来是安全的选择，但安全与明智并不相同。常见的错误包括：优化知名 GPU 而非最佳适配、忽略 VRAM 检查，以及为未实际使用的吞吐量付费。建议的起始规则是：对于较小的实验和微调，使用 RTX 4090；当需要更多 VRAM 或进行更重的推理时，转向 A100 80GB；只有在明确知道 H100 的必要性时，才考虑使用 H100。
大多数 AI 团队不需要 H100
出处: Most AI Teams Don't Need an H100
发布: 2026年3月21日
📄 English Summary
Most AI Teams Don't Need an H100
The H100 is an excellent GPU, but for many workloads, a 4090 or A100 would suffice. Many teams default to the H100 because it seems like a safe choice, but safety does not equate to sensibility. Common mistakes include optimizing for the most famous GPU instead of the best fit, skipping the VRAM check, and paying for throughput that is not actually utilized. A better starting guideline is to use the RTX 4090 for smaller experiments and fine-tunes, switch to the A100 80GB when more VRAM or heavier inference is needed, and only consider the H100 when its necessity is clearly understood.