# FluidStack vs Groq FluidStack 记录了 154,620 月访问量，月度环比增长为 +7.3%，定价为付费，定价请咨询。Groq 记录了 3,987,936 月访问量，增长率为 +10%，定价为付费。 | 指标 | [FluidStack](https://openaitools.app/zh/tool/fluidstack) | [Groq](https://openaitools.app/zh/tool/groq) | | :--- | :--- | :--- | | 官网地址 | https://fluidstack.io | https://groq.com | | 分类 | AI Developer Tools, AI Models, Large Language Models (LLMs) | AI API, Large Language Models (LLMs), Open Source AI Models | | 定价模式 | 付费，定价请咨询 | 付费 | | 月访问量 | 154,620 | 3,987,936 | | 月度环比增长率 | +7.3% | +10% | | 主要市场 | 美国 | 印度 | | 直接访问量 | 47,869 | 1,702,515 | | 评价得分 | 4.4 | 4.7 | | 收藏数 | 1 | 4 | | 支持平台 | 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. **定价与套餐:** 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. - **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. - **US-built and onshored supply chain:** Data centers are built in the United States with onshored manufacturing of compute and power infrastructure, a deliberate supply-chain and sovereignty choice. **优势:** Purpose-built AI infrastructure rather than generic cloud resale; Power, cooling and data center design handled in-house, which matters at scale; Managed provisioning and operations for large training and inference clusters; Explicit positioning on US-built, onshored infrastructure **局限:** No published self-serve pricing or instant sign-up; access requires a sales conversation; Enterprise-scale focus means very small individual workloads may not be a fit; Capacity is concentrated in US locations, which may matter for latency-sensitive or data-residency-bound teams [工具详情（Markdown）](https://openaitools.app/zh/tool/fluidstack.md) ## Groq Groq 是一个 AI 推理云，能以极低延迟运行大语言模型及其他 AI 模型。它没有把芯片设计用于训练，而是打造了专为推理优化的自研芯片 LPU，如今又加入 LPX。推理正是模型实际服务用户的环节。公司将自己定位为面向高速推理的“新云”（neocloud），并把这套硬件与软件栈和开发者 API 结合。 开发者通过 API 使用 Groq，平台托管 Llama、Mixtral、Gemma 等热门开源模型以及 Whisper 语音模型，并提供文本转语音能力。由于平台专为速度调优，常被用于实时聊天、智能体和语音交互等对响应时间敏感的场景。该 API 与常见的 OpenAI 风格请求格式高度兼容，降低了迁移成本。 Groq 扩张迅速，宣布完成 3.5 亿美元 A 轮融资，并建设数百兆瓦的推理算力。除了速度，它还强调可靠性与成本，认为对投入生产环境的团队来说，快与便宜不再需要二选一。 **定价与套餐:** 按量付费的推理 API。Groq 按 token 计费，通常提供免费开发者额度与企业级容量方案；具体费率请以官方定价页为准。 - **LPU 与 LPX 推理硬件:** 专为推理而非训练设计的自研加速器，针对极低延迟进行调优。 - **开源模型目录:** 托管 Llama、Mixtral、Gemma 等热门开源模型，以及 Whisper 语音模型。 - **高速开发者 API:** 与常见 OpenAI 风格请求格式高度兼容，便于快速集成。 - **语音与音频模型:** 提供 Whisper 自动语音识别以及文本转语音能力，适用于语音应用。 - **面向生产规模:** 为大流量生产负载构建容量，兼顾可靠性与成本。 **优势:** 面向实时应用的推理延迟极低; 提供丰富的主流开源模型; 兼容 OpenAI 的 API 降低迁移成本; 托管云服务省去自行维护 GPU 的麻烦 **局限:** 只专注推理，不涉及模型训练; 按量计费，成本随流量增长; 可用模型与选择取决于平台托管目录 [工具详情（Markdown）](https://openaitools.app/zh/tool/groq.md) ## 常见问题 ### FluidStack 和 Groq 在月流量上如何比较？ FluidStack 有 154,620 月访问量，而 Groq 有 3,987,936。流量估算描述的是受众规模，而非产品质量。 ### 它们的增长率如何比较？ FluidStack 的月度环比增长率为 +7.3%；Groq 为 +10%。 ### 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. Groq: 付费。按量付费的推理 API。Groq 按 token 计费，通常提供免费开发者额度与企业级容量方案；具体费率请以官方定价页为准。 ## 替代工具 | # | 工具名称 | 月访问量 | 月度环比增长率 | 定价模式 | 简介 | 工具详情（Markdown） | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [DeepSeek](https://openaitools.app/zh/tool/deepseek) | 372,761,591 | +4.3% | 免费增值 | 由 DeepSeek-V4 与 R1 驱动的高效开源权重与托管推理 AI，token 成本极低。 | [.md](https://openaitools.app/zh/tool/deepseek.md) | | 2 | [OpenAI 平台](https://openaitools.app/zh/tool/openai) | 234,678,639 | -9.6% | 付费 | Proprietary frontier models with powerful reasoning and multimodal features, but lacking open-weight model hosting and custom inference speeds. | [.md](https://openaitools.app/zh/tool/openai.md) | | 3 | [Google AI Studio](https://openaitools.app/zh/tool/google-ai-studio) | 112,620,020 | +2% | 免费增值 | Google 的快速原型开发 IDE 与开发者 API 工作台，用于构建基于 Gemini 模型的多模态应用。 | [.md](https://openaitools.app/zh/tool/google-ai-studio.md) | | 4 | [OpenRouter](https://openaitools.app/zh/tool/openrouter-ai) | 19,941,437 | -6.2% | 付费 | 聚合了数百个模型的统一API网关，但它更像是路由器而非直接提供硬件托管。 | [.md](https://openaitools.app/zh/tool/openrouter-ai.md) | | 5 | [fal.ai](https://openaitools.app/zh/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Delivers developer-first serverless endpoints optimized for generative media models rather than general-purpose infrastructure. | [.md](https://openaitools.app/zh/tool/fal-ai.md) | | 6 | [RunPod](https://openaitools.app/zh/tool/runpod) | 2,881,043 | +5.9% | 付费 | 提供灵活的按需 GPU 租赁和无服务器端点，但缺乏 FluidStack 那样的超大规模企业级 GPU 集群。 | [.md](https://openaitools.app/zh/tool/runpod.md) | | 7 | [Together AI](https://openaitools.app/zh/tool/together-ai) | 1,645,930 | +64.9% | 免费增值，付费 | 专为开源模型推理打造的强大云端平台，提供丰富的微调支持，但原始速度稍慢一些。 | [.md](https://openaitools.app/zh/tool/together-ai.md) | | 8 | [Vast.ai](https://openaitools.app/zh/tool/vast-ai) | 1,257,554 | +2.8% | 付费 | 提供用于低成本实验的点对点 GPU 租赁市场，不过企业级基础设施的可预测性相对较低。 | [.md](https://openaitools.app/zh/tool/vast-ai.md) | | 9 | [Modal](https://openaitools.app/zh/tool/modal-com) | 1,196,021 | +30.2% | 免费增值，定价请咨询 | 提供用于云端任务的无服务器 Python 容器运行环境，但缺乏原始多节点集群的部署控制。 | [.md](https://openaitools.app/zh/tool/modal-com.md) | | 10 | [Nebius](https://openaitools.app/zh/tool/nebius) | 1,145,711 | +10.7% | 付费，定价请咨询 | 提供专属的 NVIDIA GPU 集群和托管云基础设施，直接在企业级训练工作负载上展开竞争。 | [.md](https://openaitools.app/zh/tool/nebius.md) | --- 来源：https://openaitools.app/zh/compare/fluidstack-vs-groq 更多 Markdown 页面: [分类](https://openaitools.app/zh/categories.md) · [流量排名](https://openaitools.app/zh/rankings.md) · [llms.txt](https://openaitools.app/zh/llms.txt)