它们的增长率如何比较？

FluidStack 的月度环比增长率为 +7.3%；MyClaw 为 -23.8%。

价格如何比较？

FluidStack: 付费，定价请咨询。Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing. MyClaw: 付费。Paid subscription only, billed monthly or annually (annual saves about 17%). Tiers: Pro at roughly $17/month billed yearly ($20 monthly), Max around $34/month yearly ($40 monthly), and ULTRA near $167/month yearly ($200 monthly). Each tier bundles monthly credits with a dedicated cloud computer spec.

FluidStack 和 MyClaw 的替代方案有哪些？

相关分类中的其他工具包括 Hostinger AI 建站工具与主机, fal.ai, RunPod, Together AI, Vast.ai。

FluidStack vs MyClaw — 流量对比 (15.46万 vs 99.04万)、价格与选型结论

Open AI Tools

FluidStack vs MyClaw — 流量对比 (15.46万 vs 99.04万)、价格与选型结论 | Open AI Tools

并排流量和规格矩阵

维度 / 指标	FluidStack	MyClaw
官方域名	fluidstack.io	myclaw.ai
定价模式	付费，定价请咨询	付费
月访问量	15.46万 (154,620)	99.04万 (990,387)
月度环比流量变化	+1.05万 (+7.3%)	-30.94万 (-23.8%)
主要市场与份额	🇺🇸 美国 (95.7%)	🇺🇸 美国 (9.9%)
直接访问 / 月	4.79万	8.01万
用户评分	4.4	4.4
支持的平台	网站	网站

FluidStack

FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.

Datacenter-scale compute built in-house

FluidStack designs and builds large AI data centers, including high-density campuses with significant per-site power capacity, rather than reselling capacity from other clouds.

GPU clusters for training and inference

Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.

Power and cooling engineered together

The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.

Managed operations and reliability

Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.