# Lamini vs Scale Lamini verzeichnet 4.158 monatliche Besuche mit +0,3 % Wachstum gegenüber dem Vormonat und einem Preismodell „Freemium, Preise auf Anfrage“. Scale verzeichnet 616.915 monatliche Besuche mit +12,5 % Wachstum und einem Preismodell „Preise auf Anfrage“. | Kennzahl | [Lamini](https://openaitools.app/de/tool/lamini) | [Scale](https://openaitools.app/de/tool/scale) | | :--- | :--- | :--- | | Website-URL | https://lamini.ai | https://scale.com | | Kategorien | Large Language Models (LLMs), KI-Entwicklertools, AI Agent, KI-Textklassifizierer | KI-Entwicklertools, Large Language Models (LLMs), KI-Modelle, AI Agent | | Preismodell | Freemium, Preise auf Anfrage | Preise auf Anfrage | | Monatliche Besuche | 4.158 | 616.915 | | MoM-Wachstumsrate | +0,3 % | +12,5 % | | Primärmarkt | Vereinigte Staaten | Vereinigte Staaten | | Direkte Besuche | 1.637 | 191.408 | | Bewertungsergebnis | 4,3 | 4,7 | | Anzahl gespeicherter Einträge | 1 | 3 | | Unterstützte Plattformen | Website | Website | ## 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. **Preise und Tarife:** 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. **Stärken:** 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 **Einschränkungen:** 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 [Profile (Markdown)](https://openaitools.app/de/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. **Preise und Tarife:** 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. **Stärken:** 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. **Einschränkungen:** 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. [Profile (Markdown)](https://openaitools.app/de/tool/scale.md) ## Häufig gestellte Fragen ### Wie vergleichen sich Lamini und Scale beim monatlichen Traffic? Lamini hat 4.158 monatliche Besuche, während Scale 616.915 verzeichnet. Traffic-Schätzungen beschreiben die Publikumsgröße, nicht die Produktqualität. ### Wie vergleichen sich ihre Wachstumsraten? Lamini verzeichnet eine Wachstumsrate von +0,3 % gegenüber dem Vormonat; Scale verzeichnet +12,5 %. ### Wie vergleichen sich die Preise? Lamini: Freemium, Preise auf Anfrage. 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: Preise auf Anfrage. Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity. ## Alternativen | # | Tool-Name | Monatliche Besuche | MoM-Wachstumsrate | Preismodell | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Gemma Open Models von Google](https://openaitools.app/de/tool/gemma-open-models-by-google) | 4.900.914 | -13,5 % | Freemium, Kostenpflichtig | Googles Familie leichter Open-Weight-KI-Modelle | [.md](https://openaitools.app/de/tool/gemma-open-models-by-google.md) | | 2 | [Together AI](https://openaitools.app/de/tool/together-ai) | 1.645.930 | +64,9 % | Freemium, Kostenpflichtig | 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/de/tool/together-ai.md) | | 3 | [Roboflow](https://openaitools.app/de/tool/roboflow) | 1.431.204 | +6,6 % | Freemium, Preise auf Anfrage | Optimiert die Annotation von Computer-Vision-Datensätzen und das Modelltraining, ist jedoch weniger für allgemeine LLM-Textaufgaben geeignet. | [.md](https://openaitools.app/de/tool/roboflow.md) | | 4 | [OrcaRouter](https://openaitools.app/de/tool/orcarouter) | 975.300 | -5,2 % | Freemium | 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/de/tool/orcarouter.md) | | 5 | [Labelbox](https://openaitools.app/de/tool/labelbox) | 762.803 | -22,8 % | Preise auf Anfrage | Konzentriert sich stark auf Enterprise-Datenkennzeichnung und die Kuratierung von Trainingsdaten, ähnlich dem Kern-Annotationsgeschäft von Scale. | [.md](https://openaitools.app/de/tool/labelbox.md) | | 6 | [Vapi](https://openaitools.app/de/tool/vapi) | 662.301 | -11,4 % | Freemium | Sprach-KI-Agenten per API entwickeln, testen und produktiv einsetzen | [.md](https://openaitools.app/de/tool/vapi.md) | | 7 | [BLACKBOX.AI](https://openaitools.app/de/tool/blackbox-ai-1) | 622.975 | -27,2 % | Kostenlose Testversion, Kostenpflichtig | Vertrauenswürdige Frontier-Inferenz, durchgängig verschlüsselt | [.md](https://openaitools.app/de/tool/blackbox-ai-1.md) | | 8 | [Abliteration.ai](https://openaitools.app/de/tool/abliteration-ai) | 522.766 | +23,9 % | Freemium, Kostenpflichtig, Preise auf Anfrage | Unbeschränkte, OpenAI-kompatible LLM-API – gesteuert durch Ihre eigenen Richtlinien | [.md](https://openaitools.app/de/tool/abliteration-ai.md) | | 9 | [SuperAnnotate](https://openaitools.app/de/tool/super-annotate) | 386.034 | +37,4 % | Kostenlose Testversion, Preise auf Anfrage | Bietet multimodale Annotationen für Unternehmen und Datenmanagement-Tools, legt jedoch weniger Wert auf verwaltete Kennzeichnungsteams. | [.md](https://openaitools.app/de/tool/super-annotate.md) | | 10 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/de/tool/prompts) | 315.624 | -80,2 % | Freemium, Preise auf Anfrage, Kostenlos | Verfolge, evaluiere und liefere KI-Modelle und Agenten in einer verbundenen Umgebung. | [.md](https://openaitools.app/de/tool/prompts.md) | --- Quelle: https://openaitools.app/de/compare/lamini-vs-scale More Markdown: [Kategorien](https://openaitools.app/de/categories.md) · [Traffic-Rankings](https://openaitools.app/de/rankings.md) · [llms.txt](https://openaitools.app/de/llms.txt)