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VPS plans require Linux and SSH familiarity to get full value, but the guided setup and AI assistant lower the barrier compared to raw VPS providers like Hetzner.","Shared hosting is intentionally constrained — you run within Hostinger's stack and cannot change the server environment. VPS plans give full root access and can run any Linux workload. The range from shared to VPS covers most beginner-to-intermediate deployment needs, but there is no managed Kubernetes, serverless, or edge compute option.","LiteSpeed with NVMe SSD and built-in caching delivers strong performance for shared hosting — independent benchmarks show sub-1-second load times and 99.96%+ uptime on shared plans. KVM VPS performance is competitive for the price. Not at the level of dedicated cloud providers like DigitalOcean or Hetzner for compute-intensive workloads.","Hostinger is one of the top three most-recommended budget hosts globally, with over 3 million customers and a 4.7\u002F5 Trustpilot score. It dominates beginner and bootstrapper audiences and appears consistently in 'best cheap hosting' roundups. Less visible in developer-tool and startup-stack communities compared to cloud-native platforms.","Shared hosting creates moderate lock-in via hPanel and Hostinger-specific tooling, though WordPress sites can be migrated via standard exports. VPS instances are standard KVM Linux — fully portable to any other VPS provider. No proprietary runtime or framework dependencies on the VPS side.",{"tool_id":698,"name":699,"slug":700,"tooltip_description":701,"logo_url":702,"logo_bg":41,"pricing_model":703,"learning_curve_score":34,"popularity_score":46,"hosting_assignment_type":25,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":707,"subcategory":708,"categories":711,"subcategories":713,"flexibility_score":46,"performance_score":46,"portability_score":46,"is_featured":60,"tags":715,"score_reasonings":724,"published_date":311,"last_updated_date":341},166,"DigitalOcean","digitalocean","Developer-focused cloud platform offering VPS (Droplets), managed Kubernetes, App Platform PaaS, and managed databases. Known for simple pricing and excellent documentation.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fdigitalocean.svg",{"slug":704,"display_name":705,"description":706},"usage_based","Usage-Based","Pricing scales with consumption: API calls, data volume, compute time, or similar metered units.",{"category_id":84,"name":469,"slug":470},{"subcategory_id":277,"name":709,"slug":710},"App Hosting","app-hosting",[712],{"category_id":84,"name":469,"slug":470,"is_primary":3,"display_order":7},[714],{"subcategory_id":277,"name":709,"slug":710,"category_id":84,"is_primary":3,"display_order":7},[716,717,718,721,722,723],{"tag_id":160,"name":208,"slug":209,"tag_type":210},{"tag_id":200,"name":201,"slug":202,"tag_type":194},{"tag_id":50,"name":719,"slug":720,"tag_type":194},"Auto-scaling","auto-scaling",{"tag_id":482,"name":483,"slug":484,"tag_type":194},{"tag_id":383,"name":384,"slug":385,"tag_type":194},{"tag_id":688,"name":689,"slug":690,"tag_type":206},{"learning_curve":725,"flexibility":726,"performance":727,"popularity":728,"portability":729},"DigitalOcean is specifically designed for developers rather than enterprise ops teams. The control panel is clean, Droplets launch in under 60 seconds, and App Platform requires no infrastructure knowledge at all. Thousands of community tutorials lower the barrier for beginners.","Offers VPS, PaaS, and managed Kubernetes under one roof, covering most deployment patterns from simple static sites to complex microservices. Custom networking, firewalls, VPC peering, and a full API give teams significant control. Missing serverless functions and some niche managed services limit the ceiling slightly.","NVMe SSDs and dedicated vCPU Droplets deliver competitive single-tenant performance. The 99.99% uptime SLA holds in practice per benchmark studies. Lacks the global edge network density of Cloudflare or the ultra-low-latency primitives of AWS.","Consistently ranks in the top 5 cloud providers for developer and startup usage. Strong presence on StackOverflow, Reddit, and developer surveys. Over 600,000 active customers as of 2024. Widely used as a first production cloud by self-taught developers.","Standard Linux VMs and Docker\u002FKubernetes workloads migrate freely to any other cloud or bare metal. No proprietary runtime lock-in. Spaces is S3-compatible. App Platform lock-in is higher — migrating away requires containerizing or adapting the build pipeline.",{"tool_id":731,"name":732,"slug":733,"tooltip_description":734,"logo_url":735,"logo_bg":71,"pricing_model":736,"learning_curve_score":46,"popularity_score":84,"hosting_assignment_type":25,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":737,"subcategory":738,"categories":741,"subcategories":743,"flexibility_score":84,"performance_score":84,"portability_score":59,"is_featured":60,"tags":745,"score_reasonings":754,"published_date":311,"last_updated_date":341},50,"Amazon Web Services","aws","World's largest cloud platform with 200+ services. Market leader in infrastructure as a service (IaaS) and platform as a service (PaaS).","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Faws.png",{"slug":704,"display_name":705,"description":706},{"category_id":84,"name":469,"slug":470},{"subcategory_id":160,"name":739,"slug":740},"Cloud Providers","cloud-providers",[742],{"category_id":84,"name":469,"slug":470,"is_primary":3,"display_order":7},[744],{"subcategory_id":160,"name":739,"slug":740,"category_id":84,"is_primary":3,"display_order":7},[746,750,751,752,753],{"tag_id":747,"name":748,"slug":749,"tag_type":194},14,"Serverless","serverless",{"tag_id":50,"name":719,"slug":720,"tag_type":194},{"tag_id":482,"name":483,"slug":484,"tag_type":194},{"tag_id":383,"name":384,"slug":385,"tag_type":194},{"tag_id":419,"name":420,"slug":421,"tag_type":206},{"learning_curve":755,"flexibility":756,"performance":757,"portability":758,"popularity":759},"Vast service catalog; IAM, VPC, and networking alone can take months to master.","Hundreds of composable services with full IaC support; virtually unlimited architectural freedom.","Global infrastructure; EC2, Lambda, and CloudFront deliver performance at any scale.","Broad API surface and proprietary services create meaningful lock-in; migration is possible but costly.","Market-leading cloud provider; used by the majority of production deployments globally.",{"tool_id":761,"name":762,"slug":763,"tooltip_description":764,"logo_url":765,"logo_bg":71,"pricing_model":766,"learning_curve_score":59,"popularity_score":59,"hosting_assignment_type":25,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":767,"subcategory":768,"categories":769,"subcategories":771,"flexibility_score":84,"performance_score":84,"portability_score":59,"is_featured":60,"tags":773,"score_reasonings":780,"published_date":311,"last_updated_date":341},51,"Google Cloud Platform","gcp","Google's cloud platform with strong data, analytics, AI, and Kubernetes capabilities. The third-largest cloud provider, after AWS and Azure.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgcp.svg",{"slug":704,"display_name":705,"description":706},{"category_id":84,"name":469,"slug":470},{"subcategory_id":160,"name":739,"slug":740},[770],{"category_id":84,"name":469,"slug":470,"is_primary":3,"display_order":7},[772],{"subcategory_id":160,"name":739,"slug":740,"category_id":84,"is_primary":3,"display_order":7},[774,775,776,777,778,779],{"tag_id":200,"name":201,"slug":202,"tag_type":194},{"tag_id":747,"name":748,"slug":749,"tag_type":194},{"tag_id":50,"name":719,"slug":720,"tag_type":194},{"tag_id":482,"name":483,"slug":484,"tag_type":194},{"tag_id":383,"name":384,"slug":385,"tag_type":194},{"tag_id":169,"name":204,"slug":205,"tag_type":206},{"learning_curve":781,"flexibility":782,"performance":783,"portability":784,"popularity":785},"Slightly more approachable than AWS; BigQuery and Cloud Run have excellent documentation.","Deep service catalog; Cloud Run, GKE, and BigQuery combine freely for any architecture.","BigQuery's columnar engine handles petabyte queries in seconds; Cloud Run scales fast.","Similar to AWS; proprietary managed services create meaningful switching costs.","Strong in data and AI workloads; second or third cloud by market share in most segments.",{"hetzner":787,"hostinger":788,"digitalocean":789,"aws":790,"gcp":791},"The default. Dify's floor of 2 cores and 4 GB is a shared-vCPU server at about €19 a month, enough for a trial; for a team with knowledge bases, the 8 GB plan at about €35 leaves Weaviate and the workers room to grow. It is a plain root VPS: install Docker, check out a release, copy the example .env, replace its passwords and keys, set INIT_PASSWORD, and start the Compose file. Hourly billing makes moving up a plan a short restart.","The budget entry. The KVM 2 plan has 2 vCPUs, 8 GB of RAM, and 100 GB of NVMe at $8.99 a month on a two-year term, $14.99 at the standard rate, which is the comfortable size for the full Dify bundle. Root access is full and the panel adds weekly backups, but the volumes directory still needs its own copy before each upgrade, and HTTPS through the bundled certbot profile is your job.","Per-second billing and snapshots from the panel. The 4 GB Basic Droplet at $24 a month meets Dify's floor, and the 8 GB plan with 4 vCPUs at $48 gives a team headroom. A snapshot before each upgrade is the simplest rollback, since database migrations run when the API container starts. Managed PostgreSQL can take the database off the server later, though the apps and conversations then live on DigitalOcean's database service.","The route with an actively maintained template: the aws-samples CDK project runs Dify's services on ECS Fargate with Aurora Serverless v2 PostgreSQL and ElastiCache behind a load balancer, and wires in Bedrock models and Knowledge Bases through IAM. Its own estimate for a low-cost configuration is about $50 a month before model usage. Dify Premium on the AWS Marketplace is the other AWS route, an EC2 image that adds custom branding.","There is no maintained template here: a community Terraform configuration for Cloud Run, Cloud SQL, and Memorystore hasn't been updated since mid-2025, so most teams run the Compose file on a Compute Engine VM. A general-purpose machine with 2 vCPUs and 8 GB costs about $50 a month left on, and Dify's Vertex AI plugin reaches Google's models from the same project. It fits when the documents and the applications calling Dify already live in Google Cloud.",{},{"kind":619,"slug":470,"name":469,"href":794},"\u002Ftools\u002Fcategories\u002Fhosting-cloud",{"name":25,"tools":796,"descriptions":797,"aliases":798,"see_all":25},[],{},{},{"name":25,"tools":800,"descriptions":801,"aliases":802,"see_all":25},[],{},{},{"llm_observability":804,"model_inference":866,"model_aggregator":959,"tunnel":1019,"storage":1073},{"name":805,"tools":806,"descriptions":861,"aliases":864,"preface":865,"see_all":25},"LLM Observability",[807,839],{"tool_id":808,"name":809,"slug":810,"tooltip_description":811,"logo_url":812,"logo_bg":71,"pricing_model":813,"learning_curve_score":34,"popularity_score":59,"hosting_assignment_type":47,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":814,"subcategory":817,"categories":821,"subcategories":823,"flexibility_score":84,"performance_score":46,"portability_score":84,"is_featured":60,"tags":825,"score_reasonings":833,"published_date":312,"last_updated_date":25},296,"Langfuse","langfuse","Open-source platform for tracing, evaluating, and monitoring LLM applications and AI agents. It adds prompt management, datasets, and cost and latency analytics, and runs as a managed cloud or self-hosted.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Flangfuse.png",{"slug":43,"display_name":44,"description":45},{"category_id":379,"name":815,"slug":816},"Observability & Monitoring","observability-monitoring",{"subcategory_id":818,"name":819,"slug":820},75,"LLM & Agent Observability","llm-agent-observability",[822],{"category_id":379,"name":815,"slug":816,"is_primary":3,"display_order":7},[824],{"subcategory_id":818,"name":819,"slug":820,"category_id":379,"is_primary":3,"display_order":7},[826,827,828,829],{"tag_id":192,"name":74,"slug":193,"tag_type":194},{"tag_id":196,"name":197,"slug":198,"tag_type":194},{"tag_id":200,"name":201,"slug":202,"tag_type":194},{"tag_id":830,"name":831,"slug":832,"tag_type":206},35,"Monitoring","monitoring",{"performance":834,"learning_curve":835,"flexibility":836,"popularity":837,"portability":838},"The ClickHouse-backed analytics layer handles high trace volumes and fast dashboard queries, and SDKs send traces asynchronously so they add little latency to the application.","Framework integrations add tracing with a callback handler or a decorator, and the cloud version needs only an API key. Evaluations and datasets take more thought but are optional.","OpenTelemetry-based instrumentation, SDKs in Python and TypeScript, integrations for most agent frameworks, a public API, and a self-hostable codebase let teams wire it into nearly any stack.","Around 34K GitHub stars and the most-cited open-source option in LLM observability comparisons, well known to teams shipping LLM features but a young category that few developers outside AI work have looked at yet.","MIT-licensed core, self-hosting on any infrastructure, and OpenTelemetry instrumentation mean traces and prompts can move between the cloud and self-hosted deployments or to another OTel backend.",{"tool_id":840,"name":841,"slug":842,"tooltip_description":843,"logo_url":844,"logo_bg":41,"pricing_model":845,"learning_curve_score":34,"popularity_score":59,"hosting_assignment_type":115,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":846,"subcategory":847,"categories":848,"subcategories":850,"flexibility_score":46,"performance_score":46,"portability_score":34,"is_featured":60,"tags":852,"score_reasonings":855,"published_date":312,"last_updated_date":25},297,"LangSmith","langsmith","LangChain's platform for tracing, evaluating, and deploying LLM applications and agents. It works with any framework and is tightest with LangChain and LangGraph, adding datasets, prompt tooling, and managed agent hosting.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Flangsmith.png",{"slug":43,"display_name":44,"description":45},{"category_id":379,"name":815,"slug":816},{"subcategory_id":818,"name":819,"slug":820},[849],{"category_id":379,"name":815,"slug":816,"is_primary":3,"display_order":7},[851],{"subcategory_id":818,"name":819,"slug":820,"category_id":379,"is_primary":3,"display_order":7},[853,854],{"tag_id":200,"name":201,"slug":202,"tag_type":194},{"tag_id":830,"name":831,"slug":832,"tag_type":206},{"learning_curve":856,"flexibility":857,"performance":858,"popularity":859,"portability":860},"LangChain and LangGraph apps start tracing by setting an API key and one environment variable, and the UI is built around the concepts those frameworks already use. Evaluations and deployment add more to learn.","Covers tracing, evals, prompts, monitoring, and deployment with SDKs and OpenTelemetry for any framework, but customisation stops at what the hosted product and its API expose.","Handles production trace volumes for large LangChain customers, and its managed deployment runtime supports persistence and background runs for long agents.","The default observability choice for LangChain users and the brand most often named first in LLM tracing comparisons, but the category is still young and little known outside teams building with LLMs.","Traces and datasets live in LangChain's cloud unless an Enterprise contract pays for self-hosting, and agents on LangSmith Deployment are tied to its runtime, although OpenTelemetry ingestion eases instrumenting outside LangChain.",{"langfuse":862,"langsmith":863},"Configured per app in Dify's Monitoring page: paste a Langfuse public key, secret key, and host, and every run of that app arrives as a trace with its nodes, model calls, latency, and token cost. The host can be Langfuse Cloud or your own server, with Langfuse Self-Hosted as a stack of its own. Dify's built-in logs show what an app answered; Langfuse adds the cost and timing view across apps.","The same per-app Monitoring setting with a LangSmith API key and project, for teams already tracing other LangChain-based work there. It is a hosted, closed-source service with self-hosting on Enterprise only, so traces with prompts leave your server; the free Developer plan covers one seat and 5,000 traces a month.",{},"Add LLM observability when you want to see every model call, tool call, and token cost inside a run, so a wrong answer can be traced to the step that caused it.",{"name":867,"tools":868,"descriptions":950,"aliases":954,"preface":955,"see_all":956},"Model Inference",[869,899,925],{"tool_id":870,"name":871,"slug":872,"tooltip_description":873,"logo_url":874,"logo_bg":41,"pricing_model":875,"learning_curve_score":135,"popularity_score":84,"hosting_assignment_type":166,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":876,"subcategory":879,"categories":883,"subcategories":885,"flexibility_score":84,"performance_score":46,"portability_score":84,"is_featured":60,"tags":887,"score_reasonings":892,"published_date":341,"last_updated_date":898},210,"Ollama","ollama","The most widely used way to run open-weight LLMs locally — one command downloads and serves models like Llama, Qwen, DeepSeek, GLM, and MiniMax through an OpenAI-compatible API, with an optional paid Ollama Cloud tier for larger models than local hardware can handle.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Follama.svg",{"slug":43,"display_name":44,"description":45},{"category_id":482,"name":877,"slug":878},"AI Infrastructure","ai-infrastructure",{"subcategory_id":880,"name":881,"slug":882},60,"AI Runtime & Serving","ai-runtime-serving",[884],{"category_id":482,"name":877,"slug":878,"is_primary":3,"display_order":7},[886],{"subcategory_id":880,"name":881,"slug":882,"category_id":482,"is_primary":3,"display_order":7},[888,889,890,891],{"tag_id":192,"name":74,"slug":193,"tag_type":194},{"tag_id":196,"name":197,"slug":198,"tag_type":194},{"tag_id":200,"name":201,"slug":202,"tag_type":194},{"tag_id":375,"name":376,"slug":377,"tag_type":194},{"learning_curve":893,"flexibility":894,"performance":895,"popularity":896,"portability":897},"A single install command and a single command to pull and run a model make it the lowest-friction way to try a local LLM, with no configuration required to get started.","100+ supported models, an OpenAI-compatible API for drop-in tooling reuse, and both local and cloud execution modes give it very broad applicability across workflows.","Automatic hardware tuning and support for the latest open-weight models keep it competitive for local inference, though it is not purpose-built for high-throughput production serving the way dedicated inference servers are.","The most widely used local LLM runtime by a clear margin, with 178K+ GitHub stars, 52 million monthly downloads, and 2.5 billion+ cumulative downloads.","MIT-licensed, runs on macOS, Windows, and Linux across Apple Silicon, NVIDIA, and AMD hardware, and models are entirely self-hosted with no forced cloud dependency.","2026-09-28",{"tool_id":900,"name":901,"slug":902,"tooltip_description":903,"logo_url":904,"logo_bg":71,"pricing_model":905,"learning_curve_score":46,"popularity_score":46,"hosting_assignment_type":166,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":906,"subcategory":907,"categories":908,"subcategories":910,"flexibility_score":84,"performance_score":84,"portability_score":84,"is_featured":60,"tags":912,"score_reasonings":919,"published_date":312,"last_updated_date":25},298,"vLLM","vllm","Open-source, high-throughput inference and serving engine for large language models, exposing an OpenAI-compatible API. It is the most common way to self-host open-weight models in production on GPU and accelerator clusters.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fvllm.svg",{"slug":73,"display_name":74,"description":75},{"category_id":482,"name":877,"slug":878},{"subcategory_id":880,"name":881,"slug":882},[909],{"category_id":482,"name":877,"slug":878,"is_primary":3,"display_order":7},[911],{"subcategory_id":880,"name":881,"slug":882,"category_id":482,"is_primary":3,"display_order":7},[913,916,917,918],{"tag_id":135,"name":914,"slug":915,"tag_type":298},"Python","python",{"tag_id":192,"name":74,"slug":193,"tag_type":194},{"tag_id":196,"name":197,"slug":198,"tag_type":194},{"tag_id":169,"name":204,"slug":205,"tag_type":206},{"learning_curve":920,"flexibility":921,"performance":922,"popularity":923,"portability":924},"Starting a server is one command, but running it well in production means understanding GPU memory, KV-cache sizing, quantization, and multi-GPU parallelism, plus the Kubernetes layer around it.","Serves hundreds of model architectures with configurable quantization, parallelism, LoRA adapters, structured outputs, and speculative decoding, and can be embedded as a Python library or run as a server.","PagedAttention and continuous batching set the throughput bar that other open-source engines are measured against, and the V1 engine cut scheduling overhead further.","Around 93K GitHub stars and the engine underneath many hosted inference services, so anyone self-hosting models knows it, while developers who only call hosted APIs rarely touch it directly.","Apache-2.0, runs on GPUs and accelerators from several vendors, installs anywhere Python or Docker runs, and exposes a standard OpenAI-style API.",{"tool_id":926,"name":927,"slug":928,"tooltip_description":929,"logo_url":930,"logo_bg":71,"pricing_model":931,"learning_curve_score":135,"popularity_score":46,"hosting_assignment_type":115,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":932,"subcategory":933,"categories":937,"subcategories":939,"flexibility_score":59,"performance_score":84,"portability_score":34,"is_featured":60,"tags":941,"score_reasonings":944,"published_date":341,"last_updated_date":312},220,"Groq","groq","Fast LLM inference on Groq's own LPU hardware: unlike aggregators such as OpenRouter, Groq runs the compute itself, with low time-to-first-token and per-token pricing among the lowest of the major providers.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgroq.svg",{"slug":704,"display_name":705,"description":706},{"category_id":482,"name":877,"slug":878},{"subcategory_id":934,"name":935,"slug":936},77,"AI Inference Providers","ai-inference-providers",[938],{"category_id":482,"name":877,"slug":878,"is_primary":3,"display_order":7},[940],{"subcategory_id":934,"name":935,"slug":936,"category_id":482,"is_primary":3,"display_order":7},[942,943],{"tag_id":169,"name":204,"slug":205,"tag_type":206},{"tag_id":160,"name":208,"slug":209,"tag_type":210},{"flexibility":945,"performance":946,"popularity":947,"portability":948,"learning_curve":949},"Model catalogue is curated around what runs well on LPU hardware, narrower than a general-purpose aggregator, and there's no self-hosting or custom deployment option.","Sub-100ms time-to-first-token and a purpose-built LPU architecture make it the fastest, most consistent inference provider by a real technical margin, not just marketing.","A $650M fundraise and Nvidia's ~$20B LPU licensing deal signal strong external validation, though its curated model catalogue keeps it a step behind aggregators in raw adoption breadth.","Closed, hosted-only SaaS running on proprietary hardware, no self-hosting path and no way to replicate the LPU speed advantage outside Groq's own infrastructure.","OpenAI-compatible API and a single API key get requests flowing in minutes, no infrastructure or model-serving setup required.",{"ollama":951,"vllm":952,"groq":953},"Added through the official Ollama plugin from the Dify Marketplace, one of its most installed: give it the Ollama server's base URL, port 11434 by default, and the model names, and every app in the workspace can pick them. Dify runs in containers, so use the host's address rather than localhost. A local model needs far more memory than Dify's 4 GB floor, or a graphics card, so it belongs on a larger server or a separate machine.","For open-weight models served to many users from a GPU server: add it through Dify's OpenAI-API-compatible provider plugin with the vLLM server's \u002Fv1 address and API key, and the model becomes available to every app. vLLM serves one model per server, so each model is its own entry. vLLM Inference Server is a stack of its own.","A hosted provider of open-weight models on its own chips, added with the GroqCloud plugin and an API key. Its speed suits the many short model calls a workflow makes, such as classifying a question before retrieval, and billing is per token with a free rate-limited tier.",{},"Add model inference when you want an open-weight model in the mix: on your own hardware for privacy, or on a hosted inference provider for speed and low per-token prices.",{"kind":957,"slug":882,"name":881,"href":958},"subcategory","\u002Ftools\u002Fcategories\u002Fai-infrastructure\u002Fai-runtime-serving",{"name":960,"tools":961,"descriptions":1012,"aliases":1015,"preface":1016,"see_all":1017},"Model Aggregator",[962,987],{"tool_id":963,"name":964,"slug":965,"tooltip_description":966,"logo_url":967,"logo_bg":71,"pricing_model":968,"learning_curve_score":135,"popularity_score":46,"hosting_assignment_type":115,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":969,"subcategory":970,"categories":974,"subcategories":976,"flexibility_score":46,"performance_score":46,"portability_score":59,"is_featured":60,"tags":978,"score_reasonings":981,"published_date":341,"last_updated_date":312},218,"OpenRouter","openrouter","Unified, OpenAI-compatible API to 500+ models across 80+ providers, with automatic provider fallback and one credits-based bill: the hosted, nothing-to-deploy counterpart to a self-hosted gateway like LiteLLM.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fopenrouter.svg",{"slug":704,"display_name":705,"description":706},{"category_id":482,"name":877,"slug":878},{"subcategory_id":971,"name":972,"slug":973},63,"AI Model Aggregators","ai-model-aggregators",[975],{"category_id":482,"name":877,"slug":878,"is_primary":3,"display_order":7},[977],{"subcategory_id":971,"name":972,"slug":973,"category_id":482,"is_primary":3,"display_order":7},[979,980],{"tag_id":169,"name":204,"slug":205,"tag_type":206},{"tag_id":160,"name":208,"slug":209,"tag_type":210},{"flexibility":982,"performance":983,"portability":984,"popularity":985,"learning_curve":986},"500+ models across 80+ providers, custom data policies, and a Bring-Your-Own-Key mode cover most routing needs, though there's no control over the underlying routing logic the way a self-hosted gateway offers.","Edge-deployed routing and automatic provider fallback keep added latency low and reliability high, backed by real scale (200+ trillion tokens\u002Fmonth).","Closed-source, hosted-only SaaS with no self-hosting option, credits and API keys are OpenRouter-specific and don't transfer if switching to a self-hosted gateway.","Aggregates 400+ models from 60+ providers behind one OpenAI-style API and is usually the first stop for developers who want to try many models without juggling separate provider keys. A fixture of the LLM-app-building corner of AI development specifically, not a name outside that corner.","A single OpenAI-compatible API key and endpoint gives instant access to hundreds of models, no infrastructure setup or provider-specific integration work required.",{"tool_id":988,"name":989,"slug":990,"tooltip_description":991,"logo_url":992,"logo_bg":71,"pricing_model":993,"learning_curve_score":34,"popularity_score":46,"hosting_assignment_type":166,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":994,"subcategory":995,"categories":996,"subcategories":998,"flexibility_score":84,"performance_score":46,"portability_score":84,"is_featured":60,"tags":1000,"score_reasonings":1005,"published_date":341,"last_updated_date":1011},221,"LiteLLM","litellm","The open-source AI gateway you run yourself: one OpenAI-compatible endpoint in front of more than 100 model providers, with virtual keys, budgets, and spend tracking. 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No Dockerfile, no CLI, no YAML — connect a repo, and the platform builds and deploys automatically. The dashboard is clean and self-explanatory. Developers new to cloud deployment consistently cite Render as the easiest on-ramp to production hosting.","Covers the standard web app deployment pattern well: HTTP services, workers, cron, databases, and static sites. Docker is supported, and private networking is first-class. However the platform does not offer managed Kubernetes, GPU machines, or fine-grained infrastructure control. Advanced networking, multi-region active-active, and custom VM configurations are out of scope.","Flat-rate VMs with up to 32 GB RAM and 8 CPUs are available for demanding workloads, and zero-downtime deploys keep services live during updates. The free tier's 30–50 second cold start after inactivity is a significant limitation for demos and hobby projects, but paid tiers are always-on. 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A shared-vCPU server with 2 vCPUs and 4 GB of RAM costs about €19 a month and runs AnythingLLM with room for its built-in embedder and vector store; its x86 CPUs support the AVX2 instructions the vector store needs. That server can run only small models slowly on its CPU, so point AnythingLLM at Ollama on a machine with a graphics card, such as one you own or Hetzner's GPU servers from about €214 a month. Install Docker, mount the storage directory, and set a password before publishing anything.","The budget entry. The KVM 2 plan has 2 vCPUs, 8 GB of RAM, and 100 GB of NVMe at $8.99 a month on a two-year term, $14.99 at the standard rate, double what AnythingLLM needs, and enough to try a small quantized model on the CPU next to it, slowly. The cheaper KVM 1 has a single vCPU, below the 2-core minimum. Root access is full and the panel adds weekly backups; TLS and the password are your job.","AnythingLLM maintains a Terraform template that creates a Droplet running the container, served over plain HTTP on port 3001, so a password and a proxy for HTTPS still come after it. The template's default is the 2 GB Droplet at $18 a month, AnythingLLM's floor; the 4 GB Basic Droplet with 2 vCPUs at $24 covers the app with headroom. DigitalOcean also rents GPU Droplets, which can host the model runtime near the app when a team has no hardware of its own.","A container platform with a one-click template linked from AnythingLLM's README, using the Railway build of the image. TLS ends at the platform, so the reverse proxy or PaaS choice doesn't apply, but the instance still needs a password before it is shared. Attach a volume at the storage directory, or the database and documents go with each redeploy. Memory is billed at about $10 per GB a month on top of the $5 Hobby plan, so the app lands around $25. There is no GPU here, so the model runs elsewhere or is a hosted one.","A container platform with a Deploy to Render button in AnythingLLM's README, built from the render branch and the Render build of the image. AnythingLLM's 2 GB floor means the Standard instance, $25 a month, plus a persistent disk for the storage directory, which also keeps the service to a single instance. TLS ends at the platform, so the reverse proxy or PaaS choice doesn't apply. Render has no GPUs, so pair it with a remote runtime or a hosted model.","AnythingLLM's own CloudFormation template creates one EC2 instance with a 10 GiB volume and serves the app over plain HTTP on port 3001, so a password, a domain, and HTTPS are still to add. Its default t3.small has 2 GB, AnythingLLM's floor; a t3.medium with 2 vCPUs and 4 GB costs about $30 a month on demand. 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ChatGPT's cultural reach directly drives API adoption. Virtually every developer tool, no-code platform, and enterprise software suite lists OpenAI as a primary integration.","Entirely cloud-bound; no self-hosted option. The API is proprietary — migrating to a different provider requires rewriting prompt logic, tool schemas, and API call structure. Azure and Bedrock availability reduces cloud lock-in but not provider lock-in.","The Chat Completions API is one of the most beginner-friendly interfaces in software — a single POST request with a messages array returns a completion. Official SDKs for Python and Node ship with comprehensive docs and hundreds of cookbook examples. The main learning curve is choosing the right model family and managing costs rather than the API mechanics themselves.","OpenAI offers genuine breadth — five model families, fine-tuning (supervised + reinforcement), function calling, structured outputs, and real-time audio. However, all inference is cloud-only and proprietary; you cannot swap the underlying model weights, run locally, or choose your hardware. Compared to open-weight alternatives, customisation stops at fine-tuning.",{"tool_id":1881,"name":1882,"slug":1883,"tooltip_description":1884,"logo_url":1885,"logo_bg":71,"pricing_model":1886,"learning_curve_score":34,"popularity_score":46,"hosting_assignment_type":25,"hosting_provider_restriction":48,"hosting_target_restriction":48,"hosting_compatible_tool_ids":25,"parent_tool_id":25,"category":1887,"subcategory":1888,"categories":1889,"subcategories":1891,"flexibility_score":46,"performance_score":84,"portability_score":34,"is_featured":60,"tags":1893,"score_reasonings":1895,"published_date":311,"last_updated_date":341},159,"Google Gemini","google-gemini","Google's LLM API with a full model family, from low-cost Flash-Lite to the Gemini 3.1 Pro flagship, with 1M-token context, native multimodal input, a free tier in AI Studio, and enterprise access through Google Cloud.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgoogle-gemini.svg",{"slug":704,"display_name":705,"description":706},{"category_id":1842,"name":1832,"slug":1843},{"subcategory_id":761,"name":1845,"slug":1846},[1890],{"category_id":1842,"name":1832,"slug":1843,"is_primary":3,"display_order":7},[1892],{"subcategory_id":761,"name":1845,"slug":1846,"category_id":1842,"is_primary":3,"display_order":7},[1894],{"tag_id":160,"name":208,"slug":209,"tag_type":210},{"learning_curve":1896,"flexibility":1897,"performance":1898,"popularity":1899,"portability":1900},"Getting started is exceptionally frictionless — Google AI Studio requires only a Google account, no billing setup. The API follows standard REST conventions with well-maintained Python and JavaScript SDKs. The learning curve is low for basic usage; more advanced features like Vertex AI agent orchestration, grounding configuration, and context caching add moderate complexity.","Broad model selection (Flash-Lite to 3.1 Pro), native multimodal capabilities, function calling, structured output, code execution, and grounding with Search cover a wide range of use cases. Vertex AI adds fine-tuning and custom grounding sources. The main flexibility constraint is that all models are proprietary and cloud-hosted — no self-hosting or weights access.","Gemini 3.1 Pro leads on ARC-AGI-2 (77.1%) and outperforms GPT-5.4 on GPQA Diamond. Gemini 2.5 Flash consistently benchmarks near the top of its price tier. The 1M+ token context window is unmatched for long-document tasks. Competitive with the best frontier models across reasoning, code, and multimodal tasks as of 2026.","750M+ consumer Gemini users by early 2026 and 13M developers reported building with Google's generative models. API request volume hit 85B in January 2026 (142% YoY growth). Strong and accelerating, but OpenAI maintains a larger developer ecosystem and ChatGPT holds ~65% consumer chatbot market share vs Gemini's ~21%.","Deeply tied to Google infrastructure — the API is available only through Google AI Studio or Vertex AI (GCP). No open weights, no self-hosting, no third-party deployment. Moving workloads to another provider requires prompt re-testing and SDK changes. Vertex AI features (grounding, residency controls, agent orchestration) deepen GCP lock-in further.",{"claude":1902,"openai":1903,"google-gemini":1904},"A hosted model for when local hardware isn't enough: set Anthropic as the provider with an API key, for the whole instance or just one workspace, since AnythingLLM picks the model per workspace. Prompt caching is a single setting and cuts the cost of the instructions resent with every message. The prompts and the document passages retrieved for each answer then leave your network, which is the trade against a local model.","GPT models through an OpenAI API key, for the instance or a single workspace, with OpenAI's embedding models available as the embedder too. A reasonable choice for agent workspaces, where tool calling matters more than in plain document chat. Like every hosted provider, the retrieved document passages go to OpenAI with each question.","Gemini through a Google AI Studio key, whose rate-limited free tier is enough to try document chat before paying anything. Its long context windows suit workspaces with large documents, and Gemini embedding models can replace the built-in embedder. Retrieved passages leave your network with each question.",{},"Add a language model when the app needs an AI feature, such as summarising, classifying, drafting text, or answering questions, called through the provider's API with no other new infrastructure.",{"kind":619,"slug":1843,"name":1832,"href":1908},"\u002Ftools\u002Fcategories\u002Fllm",[1910,1913],{"slug":1135,"name":1136,"description":1137,"icon_url":1138,"addition_types":1911},[1912,1141,1843],"vector_db",{"slug":1150,"name":1151,"description":1152,"icon_url":1153,"addition_types":1914},[1155],{"exposure":1916},{"name":1917,"option_types":1918},"Reverse Proxy or PaaS",[1919,1920],"reverse_proxy","self_hosted_paas",[],1791799923072]