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| Activepieces | AnythingLLM | ComfyUI | Coze Studio | Dify | FastGPT | Firecrawl | Flowise | Jan | Khoj | Label Studio | Langflow | Langfuse | LibreChat | LibreTranslate | LiteLLM | llama.cpp | LobeHub (LobeChat) | LocalAI | MaxKB | Milvus | MinerU | n8n | NextChat | Ollama | Onyx (formerly Danswer) | Open Notebook | Open WebUI | OpenHands | Paperless-AI | PDFMathTranslate | PrivateGPT | Qdrant | RAGFlow | Sim | Speaches | Tabby | Vane (formerly Perplexica) | vLLM | whisper.cpp | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Category | Workflow automation with AI | Knowledge base & RAG | Image & media generation | AI app & agent builders | AI app & agent builders | Knowledge base & RAG | Web scraping for AI | AI app & agent builders | Private ChatGPT-style chat | AI search & research assistants | Data labeling & vector databases | AI app & agent builders | LLM gateway & observability | Private ChatGPT-style chat | Speech & translation | LLM gateway & observability | Local model runtimes | Private ChatGPT-style chat | Local model runtimes | Knowledge base & RAG | Data labeling & vector databases | Document processing | Workflow automation with AI | Private ChatGPT-style chat | Local model runtimes | Knowledge base & RAG | Knowledge base & RAG | Private ChatGPT-style chat | Coding assistants | Document processing | Speech & translation | Knowledge base & RAG | Data labeling & vector databases | Knowledge base & RAG | AI app & agent builders | Speech & translation | Coding assistants | AI search & research assistants | Local model runtimes | Speech & translation |
| What it is | Open-source Zapier alternative with AI agents, MCP and human-in-the-loop steps. | All-in-one private chat with your documents, agents and an embeddable widget. | Node-based engine for generating images, video, 3D and audio with open models. | Open-source edition of ByteDance's Coze agent-building platform. | Visual platform for building LLM apps, RAG chatbots, agents and workflows. | Knowledge-base Q&A and visual AI workflow platform. | API that turns websites into clean Markdown or structured data for LLMs. | Drag-and-drop builder for LLM agents and chatflows (archived August 2026). | Offline desktop ChatGPT alternative that runs models on each employee's computer. | Personal and team AI "second brain" for your documents and the web. | Data labeling tool for text, images, audio and video, used to build and evaluate AI models. | Visual builder for AI agents and RAG flows that you can deploy as APIs or MCP servers. | LLM observability with tracing, prompt management, evaluations and cost tracking. | Multi-provider ChatGPT-style interface with agents, file search and user management. | Self-hosted machine translation API with no dependency on Google or DeepL. | AI gateway that puts 100+ LLM providers behind one OpenAI-compatible API with keys and budgets. | Lightweight C/C++ engine that runs quantized open models on CPU or GPU, with an OpenAI-compatible server. | Polished multi-model chat and agent workspace with plugins and knowledge bases. | OpenAI-compatible API for LLMs, vision, voice and images on any hardware. | Enterprise knowledge-base and agent platform with RAG and workflows. | Scalable open-source vector database for semantic search and RAG at large data volumes. | Document parser that converts PDFs, scans and Office files into clean Markdown or JSON for LLMs and RAG. | Workflow automation with 1,500+ integrations and built-in AI agent nodes. | Lightweight ChatGPT-style web app you can run with one Docker command. | The simplest way to download and run open-weight LLMs locally behind an API. | AI chat and enterprise search connected to 50+ workplace apps. | Private, self-hosted alternative to Google NotebookLM with your choice of AI models. | Feature-rich self-hosted chat UI for Ollama and OpenAI-compatible APIs. | Self-hosted control center for AI coding agents that write code, review PRs and run automations. | AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). | PDF translator that keeps the original layout, formulas, charts and tables. | API-first private document Q&A that sits on top of your own LLM server. | Fast vector database for semantic search and RAG back-ends. | RAG engine with deep document parsing (OCR, layout and tables) and cited answers. | Visual builder for AI agent workflows, with knowledge bases, integrations and an API. | OpenAI-compatible speech-to-text and text-to-speech server (faster-whisper, Kokoro, Piper). | Self-hosted AI coding assistant (Copilot alternative) for your team. | Private, Perplexity-style AI answer engine with cited web sources. | High-throughput LLM inference server for GPUs with an OpenAI-compatible API. | Fast C/C++ port of OpenAI Whisper speech recognition with a small HTTP transcription server. |
| License | MIT (core) + Activepieces Enterprise License (ee directories) | MIT | GPL-3.0 | Apache-2.0 | Dify Open Source License (modified Apache-2.0) | FastGPT Open Source License (Apache-2.0 with conditions) | AGPL-3.0 (SDKs and some UI components MIT) | Apache-2.0 (enterprise directory under a commercial license) | Apache-2.0 | AGPL-3.0 | Apache-2.0 | MIT | MIT (core) + Langfuse Enterprise License (ee directories) | MIT | AGPL-3.0 | MIT (core) + LiteLLM Enterprise License (enterprise directory) | MIT | LobeHub Community License (Apache-2.0 with conditions) | MIT | GPL-3.0 | Apache-2.0 | MinerU Open Source License (Apache-2.0 with additional terms) | Sustainable Use License (fair-code) + n8n Enterprise License for .ee files | MIT | MIT | MIT (Community Edition) + Onyx Enterprise License (ee directories) | MIT | Open WebUI License (BSD-3-Clause style with branding clause) | MIT | MIT | AGPL-3.0 | Apache-2.0 | Apache-2.0 | Apache-2.0 | Apache-2.0 | MIT | Apache-2.0 (ee directory under a separate license) | MIT | Apache-2.0 | MIT |
| License type | Open core | Permissive | Copyleft (GPL) | Permissive | Custom / conditional | Custom / conditional | Network copyleft (AGPL) | Open core | Permissive | Network copyleft (AGPL) | Permissive | Permissive | Open core | Permissive | Network copyleft (AGPL) | Open core | Permissive | Custom / conditional | Permissive | Copyleft (GPL) | Permissive | Custom / conditional | Source-available | Permissive | Permissive | Open core | Permissive | Custom / conditional | Permissive | Permissive | Network copyleft (AGPL) | Permissive | Permissive | Permissive | Permissive | Permissive | Open core | Permissive | Permissive | Permissive |
| License conditions | Everything outside packages/ee and packages/server/api/src/app/ee is MIT. Code in those directories needs a commercial license. | Permissive. Internal and commercial use allowed; keep the copyright notice. | Free to use internally and commercially. If you distribute a modified version, you must release its source under GPL-3.0. Each model has its own license; check before commercial use. | Permissive. Internal and commercial use allowed; keep license and notices. | Commercial use is allowed, including as a backend for your own apps. Extra conditions: you may not run a multi-tenant service (one tenant = one workspace) without written permission, and you may not remove or modify the Dify logo or copyright in the frontend. | Commercial use is allowed. You need a commercial license to run a multi-tenant SaaS similar to FastGPT, or to remove or modify the logo or copyright in the console. | Free for internal and commercial use. If you modify Firecrawl and let users interact with it over a network, you must offer them the modified source under AGPL-3.0. The SDKs are MIT. | Most of the code is Apache-2.0. Code under packages/server/src/enterprise and files with explicit copyright notices are under a separate commercial license. | Permissive. Internal and commercial use allowed; keep license and notices. | Free for internal and commercial use. If you modify Khoj and let users interact with it over a network, you must offer them the modified source code under AGPL-3.0. | Permissive. Internal and commercial use allowed; keep license and notices. | Permissive. Internal and commercial use allowed; keep the copyright notice. | Everything outside ee/, web/src/ee/ and worker/src/ee/ is MIT. Those directories need a commercial license. | Permissive. Internal and commercial use allowed; keep the copyright notice. | Free for internal and commercial use. If you modify it and let users interact with it over a network, you must offer them the modified source. The name and logo are covered by separate trademark guidelines. | Everything outside the "enterprise/" directory is MIT. That directory has its own license. | Permissive. Internal and commercial use allowed. Individual models have their own licenses. | Commercial use is allowed as a frontend and backend service without modifying the source. Developing and distributing a derivative work requires a commercial license from LobeHub. | Permissive. Internal and commercial use allowed. Models keep their own licenses. | Free to use internally and commercially. If you distribute a modified version, you must release its source under GPL-3.0. | Permissive. Internal and commercial use allowed; keep license and notices. | Commercial use is allowed without a separate license, unless you and your affiliates exceed 100 million monthly active users or USD 20 million monthly revenue. If you offer an online service to third parties based on MinerU, you must state prominently that it uses MinerU. | You may use or modify n8n for your own internal business purposes or for non-commercial use. You may not sell it or offer it to others as a paid service. Files with ".ee" in the name need an n8n Enterprise License. | Permissive. Internal and commercial use allowed; keep the license notice. Branding, admin panel and permissions are sold separately as an Enterprise Edition. | Permissive. Internal and commercial use allowed. Individual models have their own licenses. | The Community Edition is MIT. Code in "ee" directories is under the Onyx Enterprise License. | Permissive. Internal and commercial use allowed; keep the license notice. | BSD-style terms plus a branding condition. You may not alter or remove the "Open WebUI" branding unless your deployment has no more than 50 end users in any rolling 30 days, you have written permission, or you hold an enterprise license. | Permissive. Internal and commercial use allowed; keep the license notice. LLM usage is billed by your model provider. | Permissive. Internal and commercial use allowed; keep the copyright notice. | Free for internal and commercial use. If you modify it and let users interact with it over a network, you must offer them the modified source under AGPL-3.0. | Permissive. Internal and commercial use allowed; keep license and notices. | Permissive. Internal and commercial use allowed; keep license and notices. | Permissive. Internal and commercial use allowed; keep license and notices. | Permissive. Internal and commercial use allowed; keep license and notices. The built-in Chat feature is a Sim-managed service that needs a Chat API key from sim.ai. | Permissive. Internal and commercial use allowed. Speech models keep their own licenses. | Everything outside the "ee/" directory is Apache-2.0. The ee/ directory has its own license. | Permissive. Internal and commercial use allowed; keep the copyright notice. | Permissive. Internal and commercial use allowed. Models keep their own licenses. | Permissive. Internal and commercial use allowed. The Whisper model weights have their own license. |
| Status | Active | Active | Active | Active | Active | Active | Active | Archived | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Active | Stale (no commit in 180+ days) | Active | Active | Active | Active | Active | Stale (no commit in 180+ days) | Active | Active | Active | Active |
| GitHub stars | 25.2k | 67.4k | 142k | 21.7k | 159k | 29.9k | 194k | 55.5k | 45.0k | 37.8k | 28.5k | 156k | 36.2k | 46.1k | 17.1k | 61.8k | 132k | 83.4k | 49.8k | 23.0k | 46.5k | 82.3k | 208k | 88.9k | 184k | 32.8k | 40.5k | 156k | 91.5k | 6.0k | 37.8k | 57.6k | 35.2k | 92.6k | 29.9k | 3.7k | 33.9k | 37.6k | 95.1k | 54.6k |
| Last commit | Oct 22, 2026 | Oct 22, 2026 | Oct 22, 2026 | Jul 29, 2026 | Oct 22, 2026 | Oct 22, 2026 | Oct 22, 2026 | Aug 13, 2026 | Oct 22, 2026 | Aug 2, 2026 | Oct 22, 2026 | Oct 21, 2026 | Oct 22, 2026 | Oct 22, 2026 | Oct 12, 2026 | Oct 22, 2026 | Oct 22, 2026 | Oct 22, 2026 | Oct 21, 2026 | Oct 21, 2026 | Oct 22, 2026 | Oct 11, 2026 | Oct 22, 2026 | Oct 20, 2026 | Oct 22, 2026 | Oct 22, 2026 | Oct 5, 2026 | Oct 16, 2026 | Oct 22, 2026 | Mar 31, 2026 | Oct 22, 2026 | Oct 20, 2026 | Oct 21, 2026 | Oct 22, 2026 | Oct 22, 2026 | Apr 18, 2026 | Jun 30, 2026 | Sep 1, 2026 | Oct 22, 2026 | Oct 19, 2026 |
| Latest release | 0.92.3 | v1.18.0 | v0.42.1 | v0.5.1 | 1.17.1 | v4.17.2 | v2.11.0 | flowise@3.1.4 | v0.8.7 | 2.0.0-beta.28 | 1.23.2 | v1.12.7 | v4.67.0 | — | v1.9.6 | v1.106.2 | v0.7.0 | v2.2.20 | v4.11.0 | v2.10.8-lts | v3.0.3 | mineru-4.0.12-released | n8n@2.44.6 | v2.16.1 | v0.40.8 | v4.9.2 | v1.15.0 | v0.12.3 | v1.30.1 | v3.0.9 | v1.9.11 | v1.0.1 | v1.19.2 | v1.0.0-rc2 | v0.9.31 | v0.9.0-rc.3 | v0.32.0 | v1.12.2 | v0.32.0 | v1.9.5 |
| Minimum hardware | Not published | 2 vCPU · 2 GB RAM · 5 GB disk | 8 GB RAM | 2 vCPU · 4 GB RAM | 2 vCPU · 4 GB RAM | 2 vCPU · 4 GB RAM | Not published | Not published | 8 GB RAM · 10 GB disk | Not published | 8 GB RAM | 1 vCPU · 1.5 GB RAM | Not published | 1 vCPU · 1 GB RAM | Not published | 1 vCPU · 4 GB RAM | Not published | 2 vCPU · 4 GB RAM · 20 GB disk | Not published | 4 vCPU · 8 GB RAM · 100 GB disk | 8 GB RAM | 2 GB RAM | Not published | Not published | Not published | 4 vCPU · 10 GB RAM · 32 GB disk | 4 GB RAM | Not published | Not published | Not published | Not published | Not published | Not published | Not published | 2 vCPU · 12 GB RAM · 20 GB disk | Not published | Not published | Not published | Not published | Not published |
| Recommended hardware | Not published | Not published | Not published | Not published | Not published | 2 vCPU · 8 GB RAM | Not published | Not published | 16 GB RAM | Not published | 16 GB RAM · 50 GB disk | 2 vCPU · 4 GB RAM | 4 vCPU · 16 GB RAM · 100 GB disk | 2 GB RAM | Not published | Not published | Not published | 4 vCPU · 8 GB RAM · 50 GB disk | Not published | Not published | 4 vCPU · 16 GB RAM | Not published | Not published | Not published | Not published | 8 vCPU · 16 GB RAM · 500 GB disk | Not published | Not published | 2 vCPU · 4 GB RAM | Not published | Not published | Not published | Not published | 4 vCPU · 16 GB RAM · 50 GB disk | 4 vCPU · 16 GB RAM · 50 GB disk | Not published | Not published | Not published | Not published | Not published |
| RAM measured by us | 1.3 GiB idle, 2.4 GiB working (our test, v0.92.3, Oct 22, 2026) | 274 MiB idle, 915 MiB working (our test, v1.18.0, Oct 22, 2026) | Not tested yet | Not tested yet | Not tested yet | Not tested yet | Not tested yet | Not tested yet | Not tested yet | Not tested yet | Not tested yet | 1.2 GiB idle, 1.3 GiB working (our test, v1.12.7, Oct 22, 2026) | Not tested yet | 750 MiB idle, 941 MiB working (our test, v0.8.8, Oct 22, 2026) | 254 MiB idle, 2.7 GiB working (our test, v1.9.6, Oct 22, 2026) | Not tested yet | 437 MiB idle, 489 MiB working (our test, vbuild 11804 (c7fc50941), Oct 22, 2026) | Not tested yet | Not tested yet | Not tested yet | Not tested yet | Not tested yet | 412 MiB idle, 607 MiB working (our test, v2.44.6, Oct 22, 2026) | 42 MiB idle, 57 MiB working (our test, v2.16.1, Oct 22, 2026) | 85 MiB idle, 1.9 GiB working (our test, v0.40.8, Oct 22, 2026) | Not tested yet | Not tested yet | 896 MiB idle, 909 MiB working (our test, v0.12.3, Oct 22, 2026) | Not tested yet | Not tested yet | Not tested yet | Not tested yet | 42 MiB idle, 566 MiB working (our test, v1.20.0, Oct 22, 2026) | Not tested yet | Not tested yet | 150 MiB idle, 1.4 GiB working (our test, vlatest-cpu (pyproject 0.1.0), Oct 22, 2026) | Not tested yet | Not tested yet | Not tested yet | Not tested yet |
| GPU | Not required / not stated | Not required / not stated | The README claims it can run even the largest open models on as little as 4 GB VRAM plus 8 GB RAM using weight streaming. NVIDIA, AMD, Intel, Apple Silicon and Ascend are supported. | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | 6 GB VRAM minimum for GPU acceleration | Only for offline chat with local models. 16 GB VRAM recommended; an NVIDIA/AMD GPU or an Apple M1+ machine speeds up responses significantly. | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Optional CUDA 12.4.1 acceleration via docker-compose.cuda.yml. | Not required / not stated | Optional. Runs on CPU (AVX/AVX2/AVX512/AMX, ARM NEON) and supports CPU+GPU hybrid inference for models larger than VRAM. Docker images exist for CUDA, ROCm, SYCL, Vulkan, MUSA and OpenVINO. | Not required / not stated | Optional. Images exist for NVIDIA CUDA 12/13, AMD ROCm, Intel oneAPI and CPU-only. | Not required / not stated | Not required / not stated | Optional. The basic tier runs ONNX models on CPU; the standard/advanced tiers work on CPU with 8 GB RAM (Vulkan recommended). PyTorch and vLLM/lmdeploy engines need a GPU with 8 GB+ VRAM and 16 GB RAM. The official Docker image targets NVIDIA GPUs only. | Not required / not stated | Not required / not stated | NVIDIA GPUs need compute capability 5.0+ and driver 550+ (570+ for compute capability 5.0–6.2). CPU-only also works. | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Not required / not stated | Optional (CUDA image). A CPU image is available. | NVIDIA GPU recommended. CodeLlama-7B in int8 needs about 8 GB VRAM. int8 needs compute capability 7.0+ (or 6.1), float16 7.0+, bfloat16 8.0+. | Not required / not stated | NVIDIA: compute capability 7.5 or higher (e.g. T4, RTX 20xx, A100, L4, H100, B200). | Optional. The default Docker image runs on CPU; CUDA, Vulkan and MUSA images are available. |
| Est. server cost | from €35.99/mo (based on our test, not official) | from €19.99/mo | GPU server (not estimated) | from €19.99/mo | from €19.99/mo | from €19.99/mo (recommended spec: €35.99/mo) | Not estimated | Not estimated | No server (desktop app) | Not estimated | from €35.99/mo (recommended spec: €69.99/mo) | from €11.99/mo (recommended spec: €19.99/mo) | from €69.99/mo | from €6.49/mo (recommended spec: €11.99/mo) | from €35.99/mo (based on our test, not official) | from €19.99/mo | from €11.99/mo (based on our test, not official) | from €19.99/mo (recommended spec: €35.99/mo) | Not estimated | from €35.99/mo | from €35.99/mo (recommended spec: €69.99/mo) | from €11.99/mo | from €11.99/mo (based on our test, not official) | from €6.49/mo (based on our test, not official) | from €19.99/mo (based on our test, not official) | from €69.99/mo | from €19.99/mo | from €11.99/mo (based on our test, not official) | from €19.99/mo | Not estimated | Not estimated | Not estimated | from €11.99/mo (based on our test, not official) | from €69.99/mo | from €69.99/mo | from €19.99/mo (based on our test, not official) | GPU server (not estimated) | Not estimated | GPU server (not estimated) | Not estimated |
| Deploy method | Docker (single container, embedded DB) | Docker | Desktop app or manual install | Docker Compose | Docker Compose | Docker Compose (install script) | Docker Compose (build from source) | npm or Docker Compose | Desktop installer | Docker Compose | Docker | Docker | Docker Compose | Docker Compose | Docker (run script) or pip | Docker | Docker (or install script / prebuilt binaries) | Docker Compose (setup script) | Docker | Docker | Docker Compose (standalone) | Python package (uv/pip) with web UI; Docker Compose for NVIDIA GPUs | Docker | Docker | Docker (or install script) | Install script (Docker Compose) | Docker Compose | Docker | Docker (or npm package) | Docker | Docker | uv (Python) or Docker | Docker | Docker Compose | Docker Compose (setup wizard or manual) | Docker | Docker (CUDA) | Docker | pip / uv (or Docker) | Docker |
| Known gotchas | 3 listed | 2 listed | 2 listed | 2 listed | 2 listed | 2 listed | 3 listed | 3 listed | 2 listed | 2 listed | 1 listed | 2 listed | 2 listed | 2 listed | 2 listed | 2 listed | 3 listed | 3 listed | 1 listed | 2 listed | 4 listed | 4 listed | 2 listed | 3 listed | 2 listed | 2 listed | 4 listed | 2 listed | 4 listed | 2 listed | 3 listed | 2 listed | 1 listed | 2 listed | 4 listed | 1 listed | 2 listed | 2 listed | 1 listed | 3 listed |
| Telemetry | On by default | On by default | Not documented | Not documented | On by default | Not documented | Off by default (opt-in) | Not documented | Off by default (opt-in) | On by default | On by default | On by default | On by default | Not documented | Not documented | None (documented) | Not documented | Not documented | Not documented | Not documented | Not documented | On by default | On by default | Not documented | Not documented | On by default | Not documented | Off by default (opt-in) | Not documented | Not documented | Not documented | Not documented | On by default | Not documented | On by default | Not documented | On by default | Not documented | On by default | Not documented |
| Calls home by default | Not documented | No (documented) | No (documented) | Not documented | Yes, by default | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Yes, by default | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Yes, by default | Not documented | Yes, by default | Not documented | Not documented | Yes, by default | Not documented | Not documented | Yes, by default | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Paid / enterprise only (SAML paid) | Not documented | Not documented | Not documented | Paid / enterprise only | Paid / enterprise only | Not documented | Paid / enterprise only (OIDC paid) | Not documented | Not documented | Paid / enterprise only (OIDC paid · SAML paid · LDAP paid) | Free (OIDC free) | Free (OIDC free) | Free (OIDC free · SAML free · LDAP free) | Not documented | Free with limits (OIDC free with limits · SAML free with limits) | Not documented | Free (OIDC free) | Free (OIDC free) | Paid / enterprise only (OIDC paid · SAML paid · LDAP paid) | Not documented | Not documented | Paid / enterprise only (OIDC paid · SAML paid · LDAP paid) | Not documented | Not documented | Not documented | Not supported (OIDC not supported · SAML not supported · LDAP not supported) | Free (OIDC free · LDAP free) | Not documented | Not documented | Not documented | Paid / enterprise only (LDAP paid) | Not applicable | Free (OIDC free) | Free (OIDC free · SAML free) | Not documented | Paid / enterprise only (LDAP paid) | Not documented | Not documented | Not documented |
| Audit log | Paid / enterprise only | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Not documented | Paid / enterprise only | Yes, free | Paid / enterprise only | Not documented | Not documented | Paid / enterprise only | Not documented | Not documented | Not documented | Paid / enterprise only | Not documented | Not documented | Paid / enterprise only | Not documented | Not documented | Not documented | No | Yes, free | Not documented | Not documented | Not documented | Paid / enterprise only | Yes, free | Not documented | Yes, free | Not documented | Not documented | Not documented | Not documented | Not documented |
| RBAC | Paid / enterprise only | Not documented | Not documented | Not documented | Basic free, more in paid plan | Paid / enterprise only | Not documented | Paid / enterprise only | Not documented | Not documented | No | No | Basic free, more in paid plan | Not documented | Not documented | Paid / enterprise only | Not documented | Not documented | Yes, free | Paid / enterprise only | Yes, free | Not documented | Paid / enterprise only | Not documented | Not documented | Paid / enterprise only | No | Yes, free | Not documented | Not documented | Not documented | Paid / enterprise only | Yes, free | Basic free, more in paid plan | Yes, free | Not documented | Not documented | Not documented | Not documented | Not documented |
| Details | Full Activepieces guide → | Full AnythingLLM guide → | Full ComfyUI guide → | Full Coze Studio guide → | Full Dify guide → | Full FastGPT guide → | Full Firecrawl guide → | Full Flowise guide → | Full Jan guide → | Full Khoj guide → | Full Label Studio guide → | Full Langflow guide → | Full Langfuse guide → | Full LibreChat guide → | Full LibreTranslate guide → | Full LiteLLM guide → | Full llama.cpp guide → | Full LobeHub (LobeChat) guide → | Full LocalAI guide → | Full MaxKB guide → | Full Milvus guide → | Full MinerU guide → | Full n8n guide → | Full NextChat guide → | Full Ollama guide → | Full Onyx (formerly Danswer) guide → | Full Open Notebook guide → | Full Open WebUI guide → | Full OpenHands guide → | Full Paperless-AI guide → | Full PDFMathTranslate guide → | Full PrivateGPT guide → | Full Qdrant guide → | Full RAGFlow guide → | Full Sim guide → | Full Speaches guide → | Full Tabby guide → | Full Vane (formerly Perplexica) guide → | Full vLLM guide → | Full whisper.cpp guide → |
Popular comparisons
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