# Lamini vs Scale Lamini 记录了 4,158 月访问量，月度环比增长为 +0.3%，定价为免费增值，定价请咨询。Scale 记录了 616,915 月访问量，增长率为 +12.5%，定价为定价请咨询。 | 指标 | [Lamini](https://openaitools.app/zh/tool/lamini) | [Scale](https://openaitools.app/zh/tool/scale) | | :--- | :--- | :--- | | 官网地址 | https://lamini.ai | https://scale.com | | 分类 | Large Language Models (LLMs), AI Developer Tools, AI Agent, AI 文本分类工具 | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent | | 定价模式 | 免费增值，定价请咨询 | 定价请咨询 | | 月访问量 | 4,158 | 616,915 | | 月度环比增长率 | +0.3% | +12.5% | | 主要市场 | 美国 | 美国 | | 直接访问量 | 1,637 | 191,408 | | 评价得分 | 4.3 | 4.7 | | 收藏数 | 1 | 3 | | 支持平台 | 网站 | 网站 | ## Lamini Lamini is an enterprise LLM platform for building, fine-tuning, controlling and deploying custom large language models. It targets teams that need their own accurate, private models rather than a generic API: you bring your data, fine-tune open models on the platform, and serve them with tuned runtimes designed to reduce hallucinations. It covers use cases like text-to-SQL, classification, RAG and function calling, and is known for running workloads on AMD GPUs. **定价与套餐:** Freemium entry point with enterprise pricing available on request. Pricing is sales-led for scaled deployments; check the official Lamini site for the current free tier, plan details and enterprise terms. - **Custom model fine-tuning:** Train and fine-tune open large language models on your own domain data so output matches your vocabulary, formats and policies. - **Hallucination reduction:** Tuned inference runtimes and grounding techniques aimed at cutting hallucinations and raising accuracy on domain-specific tasks. - **RAG, text-to-SQL and classification:** Supports common enterprise patterns — retrieval-augmented generation, text-to-SQL, text classification and function calling. - **AMD GPU acceleration:** Run training and inference workloads on AMD GPUs as an alternative GPU supply path for LLM workloads. - **Secure, controlled deployment:** Develop and serve models in an enterprise-oriented environment that keeps data and model control with your team. **优势:** Purpose-built for custom, high-accuracy LLMs rather than one-size-fits-all APIs; Explicit focus on reducing hallucinations and improving domain accuracy; Supports the enterprise staples: RAG, text-to-SQL, classification and function calling; AMD GPU workloads offer an alternative to single-vendor GPU supply **局限:** The marketed endpoints can be expensive at scale and pricing is sales-led, so you need a conversation to budget enterprise use; Deployment and fine-tuning workflows assume ML engineering skills, so it is not a no-code tool; You are tied into its ecosystem and runtimes for training and serving; Small teams without an existing data pipeline will find setup and data preparation heavy [工具详情（Markdown）](https://openaitools.app/zh/tool/lamini.md) ## Scale Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations. **定价与套餐:** Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity. - **Data Engine:** Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require. - **Model evaluation & benchmarks:** Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers. - **Enterprise AI applications:** Platform and services teams that pick the right use case, build the system and take ownership of the outcome. - **Agentic deployment:** Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations. - **Domain expertise:** Programmes spanning healthcare, robotics, defence, public sector and enterprise with human oversight built in. **优势:** Backed by a long track record in training data and model evaluation.; End-to-end coverage from data sourcing through to deployed systems.; Experienced with regulated, classified and safety-critical environments.; Benchmarks and leaderboards give an independent view of model capability. **局限:** No public pricing or self-serve signup - you need a sales conversation to get started.; Enterprise-scale contracting and data operations require real internal commitment.; Overkill for small teams with modest data or evaluation needs.; Some projects involve sensitive government and defence work with strict compliance overhead. [工具详情（Markdown）](https://openaitools.app/zh/tool/scale.md) ## 常见问题 ### Lamini 和 Scale 在月流量上如何比较？ Lamini 有 4,158 月访问量，而 Scale 有 616,915。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？ Lamini 的月度环比增长率为 +0.3%；Scale 为 +12.5%。 ### 价格如何比较？ Lamini: 免费增值，定价请咨询。Freemium entry point with enterprise pricing available on request. Pricing is sales-led for scaled deployments; check the official Lamini site for the current free tier, plan details and enterprise terms. Scale: 定价请咨询。Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity. ## 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 | [Google Gemma 开源模型](https://openaitools.app/zh/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | 免费增值，付费 | Google 的轻量级开放权重 AI 模型家族 | [.md](https://openaitools.app/zh/tool/gemma-open-models-by-google.md) | | 2 | [Together AI](https://openaitools.app/zh/tool/together-ai) | 1,645,930 | +64.9% | 免费增值，付费 | Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all b | [.md](https://openaitools.app/zh/tool/together-ai.md) | | 3 | [Roboflow](https://openaitools.app/zh/tool/roboflow) | 1,431,204 | +6.6% | 免费增值，定价请咨询 | 简化计算机视觉数据集标注与模型训练，但不太适合通用的 LLM 文本任务。 | [.md](https://openaitools.app/zh/tool/roboflow.md) | | 4 | [OrcaRouter](https://openaitools.app/zh/tool/orcarouter) | 975,300 | -5.2% | 免费增值 | OrcaRouter is an OpenAI-compatible AI gateway that grades every prompt and routes it to the best-value model, then layers on failover, guardrails, an agent firewall, and compliance tooling for production AI. | [.md](https://openaitools.app/zh/tool/orcarouter.md) | | 5 | [Labelbox](https://openaitools.app/zh/tool/labelbox) | 762,803 | -22.8% | 定价请咨询 | 专注于企业级数据标注和训练数据整理，类似于 Scale 的核心标注业务。 | [.md](https://openaitools.app/zh/tool/labelbox.md) | | 6 | [Vapi](https://openaitools.app/zh/tool/vapi) | 662,301 | -11.4% | 免费增值 | 通过 API 构建、测试并部署生产级语音 AI 智能体 | [.md](https://openaitools.app/zh/tool/vapi.md) | | 7 | [BLACKBOX.AI](https://openaitools.app/zh/tool/blackbox-ai-1) | 622,975 | -27.2% | 免费试用，付费 | 高可信前沿推理，端到端加密 | [.md](https://openaitools.app/zh/tool/blackbox-ai-1.md) | | 8 | [Abliteration.ai](https://openaitools.app/zh/tool/abliteration-ai) | 522,766 | +23.9% | 免费增值，付费，定价请咨询 | 不受限、兼容 OpenAI 的 LLM API，由你自己的策略治理 | [.md](https://openaitools.app/zh/tool/abliteration-ai.md) | | 9 | [SuperAnnotate](https://openaitools.app/zh/tool/super-annotate) | 386,034 | +37.4% | 免费试用，定价请咨询 | 提供企业级多模态标注和数据管理工具，但对托管式标注人力的强调较少。 | [.md](https://openaitools.app/zh/tool/super-annotate.md) | | 10 | [Weights & Biases（CoreWeave Forge）](https://openaitools.app/zh/tool/prompts) | 315,624 | -80.2% | 免费增值，定价请咨询，免费 | 在互联环境中跟踪、评估并交付 AI 模型与智能体。 | [.md](https://openaitools.app/zh/tool/prompts.md) | --- 来源：https://openaitools.app/zh/compare/lamini-vs-scale 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)