# Groq vs Openlayer Groq 记录了 3,987,936 月访问量，月度环比增长为 +10%，定价为付费。Openlayer 记录了 48,415 月访问量，增长率为 -6.4%，定价为免费增值，定价请咨询。 | 指标 | [Groq](https://openaitools.app/zh/tool/groq) | [Openlayer](https://openaitools.app/zh/tool/openlayer) | | :--- | :--- | :--- | | 官网地址 | https://groq.com | https://www.openlayer.com | | 分类 | AI API, Large Language Models (LLMs), Open Source AI Models | AI 测试, AI 监控, Large Language Models (LLMs), AI Developer Tools | | 定价模式 | 付费 | 免费增值，定价请咨询 | | 月访问量 | 3,987,936 | 48,415 | | 月度环比增长率 | +10% | -6.4% | | 主要市场 | 印度 | 美国 | | 直接访问量 | 1,702,515 | 25,940 | | 评价得分 | 4.7 | 4.4 | | 收藏数 | 4 | 1 | | 支持平台 | 网站 | 网站 | ## 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) ## Openlayer Openlayer is a platform that tests AI systems before release, monitors them in production, and enforces policy and compliance requirements across every model and agent your company runs. **定价与套餐:** Openlayer offers a free Basic plan covering one member, five projects, 20,000 monthly requests, three months of data retention, the AI test library, CI/CD integration, observability, alerting, and community support. The Enterprise plan is custom-quoted and adds unlimited members and projects, role-based access control, SAML SSO, explainability, data annotation, custom retention, on-premise deployment, compliance reporting, a 99.99% SLA, and white-glove onboarding. - **AI test library and custom evals:** Dozens of pre-built evaluations cover quality, safety, security, and performance, with LLM-as-a-judge scorers, session-level metrics, and support for writing your own custom tests against your own data. - **CI/CD regression testing:** Import a repository and run evaluation suites automatically on every change, benchmark each iteration, and block releases when a metric regresses beyond the threshold you define. - **Observability, tracing, and cost analytics:** Trace every request through multi-step agent workflows, including tool calls and retriever steps, with token counts, latency, cost per request, alerting integrations, and subpopulation analysis. - **Governance registry and lifecycle gates:** Register each AI system with an owner, purpose, data sensitivity, and risk tier, score inherent risk across multiple dimensions, and move systems through staged approval gates before they reach production. - **Compliance mapping and audit evidence:** Built-in frameworks such as the EU AI Act and NIST AI RMF turn policy into tracked rules, so you can see progress per project and export the evidence regulators and auditors ask for. **优势:** Covers the full loop from pre-release testing to production monitoring and governance in one platform; Strong compliance and risk-mapping capability built for regulated industries; Generous free Basic plan makes evaluation tooling accessible to small teams; CI/CD integration lets quality gates block releases automatically **局限:** Enterprise pricing is custom-quoted, so costs are not transparent up front; Compliance reporting and the deepest governance features sit behind the Enterprise plan; The breadth of layers can be a lot to adopt at once for teams that only need basic evals; Small free plan limits (one member, five projects) make it a try-it tier rather than a team plan [工具详情（Markdown）](https://openaitools.app/zh/tool/openlayer.md) ## 常见问题 ### Groq 和 Openlayer 在月流量上如何比较？ Groq 有 3,987,936 月访问量，而 Openlayer 有 48,415。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？ Groq 的月度环比增长率为 +10%；Openlayer 为 -6.4%。 ### 价格如何比较？ 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。 Openlayer: 免费增值，定价请咨询。Openlayer offers a free Basic plan covering one member, five projects, 20,000 monthly requests, three months of data retention, the AI test library, CI/CD integration, observability, alerting, and community support. The Enterprise plan is custom-quoted and adds unlimited members and projects, role-based access control, SAML SSO, explainability, data annotation, custom retention, on-premise deployment, compliance reporting, a 99.99% SLA, and white-glove onboarding. ## 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 | [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) | | 6 | [Cerebras](https://openaitools.app/zh/tool/cerebras) | 701,013 | -12.6% | 定价请咨询 | 采用晶圆级硬件的云端服务，具备媲美 Groq 的超快 Token 生成速度，但支持的模型目录较为专门。 | [.md](https://openaitools.app/zh/tool/cerebras.md) | | 7 | [Fireworks](https://openaitools.app/zh/tool/fireworks-ai) | 659,687 | +6% | 定价请咨询 | 针对开源模型的高吞吐量无服务器推理，具备优异的速度、微调能力与广泛的 API 兼容性。 | [.md](https://openaitools.app/zh/tool/fireworks-ai.md) | | 8 | [DeepInfra](https://openaitools.app/zh/tool/deep-infra) | 457,810 | -8.9% | 付费 | 成本低廉的无服务器推理云端，托管数百个开源权重模型，但缺少 LPU 等专门的自定义硬件加速器。 | [.md](https://openaitools.app/zh/tool/deep-infra.md) | | 9 | [Novita AI](https://openaitools.app/zh/tool/novita-ai) | 271,371 | -10.4% | 付费 | 提供无服务器模型 API 与 GPU 实例的 AI 云端平台，但对超低延迟文本生成的着墨较少。 | [.md](https://openaitools.app/zh/tool/novita-ai.md) | | 10 | [Chutes](https://openaitools.app/zh/tool/chutes) | 250,187 | -15.2% | 付费 | Decentralized serverless inference platform hosting open-source models, offering lower costs but less enterprise reliability guarantees. | [.md](https://openaitools.app/zh/tool/chutes.md) | --- 来源：https://openaitools.app/zh/compare/groq-vs-openlayer 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)