
根据功能和用途,为你挑选 12 款 Salad 的替代工具。
| 排名 | 工具和标语 | 官方域名 | 月访问量 | 月度增长 (MoM) |
|---|
| 定价模式 |
|---|
| 主要市场 |
|---|
| 评分 |
|---|
| 比较 |
|---|
| ● | Salad | salad.com | 71.35万 | 6.75万 (+10.4%) | 免费试用,付费,定价请咨询 | 美国 | 4.3 | 概览 |
| 1 | RunPod | runpod.io | 288.1万 | 16.15万 (+5.9%) | 付费 | 美国 | 4.7 | 比较 |
| 2 | Vast.ai | vast.ai | 125.76万 | 3.42万 (+2.8%) | 付费 | 美国 | 4.6 | 比较 |
| 3 | Modal | modal.com | 119.6万 | 27.72万 (+30.2%) | 免费增值,定价请咨询 | 美国 | 4.8 | 比较 |
| 4 | Nebius | nebius.com | 114.57万 | 11.08万 (+10.7%) | 付费,定价请咨询 | 美国 | 4.5 | 比较 |
| 5 | Cerebrium | cerebrium.ai | 2.7万 | -2.78万 (-50.8%) | 免费试用,付费 | 美国 | 4.3 | 比较 |
| 6 | Together AI | together.ai | 164.59万 | 64.77万 (+64.9%) | 免费增值,付费 | 美国 | 4.7 | 比较 |
| 7 | DeepInfra | deepinfra.com | 45.78万 | -4.45万 (-8.9%) | 付费 | 美国 | 4.6 | 比较 |
| 8 | Thunder Compute | thundercompute.com | 10.21万 | -4.17万 (-29%) | Paid (per-minute instances, per-second sandboxes) | 美国 | 4.4 | 比较 |
| 9 | TensorDock | tensordock.com | 1.97万 | -5977 (-23.3%) | 付费 | 美国 | 4.2 | 比较 |
| 10 | FluidStack | fluidstack.io | 15.46万 | 1.05万 (+7.3%) | 付费,定价请咨询 | 美国 | 4.4 | 比较 |
| 11 | Massed Compute | massedcompute.com | 1.18万 | -2.1万 (-64.1%) | 付费,定价请咨询 | 美国 | 4.2 | 比较 |
| 12 | Anyscale | anyscale.com | 4.98万 | -1.5万 (-23.2%) | 付费,定价请咨询 | 美国 | 4.6 | 比较 |
提供价格更低廉的广泛 P2P GPU 市场,但需要较多手动配置。
专项更强为 AI 流水线提供轻松的 Python 无服务器执行,但专注于 Function-as-a-Service 而非裸机虚拟机。
专项更强为 AI 流水线提供轻松的 Python 无服务器执行,但专注于 Function-as-a-Service 而非裸机虚拟机。
提供企业级 NVIDIA GPU 集群与托管式 ML 工具,但专业价格定位较高。

专项更强专门提供开源模型的托管式无服务器推理 API,而非单纯租赁 GPU 基础设施。

专项更强Offers extremely cheap serverless model hosting via API, but does not provide raw containerized GPU instances.

Features second-billed persistent SSH GPU instances, but lacks a distributed consumer hardware backbone.
Features second-billed persistent SSH GPU instances, but lacks a distributed consumer hardware backbone.

Gives access to competitive cloud GPU virtual machines, but operates traditional data centers instead of P2P.
Gives access to competitive cloud GPU virtual machines, but operates traditional data centers instead of P2P.

Focuses on large-scale enterprise GPU clusters for training, rather than lightweight consumer container workloads.
Focuses on large-scale enterprise GPU clusters for training, rather than lightweight consumer container workloads.

Delivers high-performance bare metal servers and clusters, but lacks a consumer-grade low-cost tier.
Delivers high-performance bare metal servers and clusters, but lacks a consumer-grade low-cost tier.

专项更强Scales distributed Ray workloads effortlessly across clusters, but is tailored for heavy data engineering and training.
专项更强Scales distributed Ray workloads effortlessly across clusters, but is tailored for heavy data engineering and training.