Local tools for asking questions of your own documents
RAGShelf compares 34 self-hosted and desktop tools that let a local model answer questions from your PDFs, Office files, scans, and notes, without sending them to the cloud. Filter by license, hardware, document type, and whether it can run fully offline.
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| Tool | Hardware | Fully offline |
|---|---|---|
| AnythingLLM Active | Desktop or Docker; built-in engine runs CPU or GPU (NVIDIA CUDA, AMD/Intel Vulkan) | ✅ Yes |
| Cherry Studio Active | Desktop app (Windows, macOS, Linux) | ✅ Yes |
| Dify Active | Docker; minimum 2 CPU cores, 4GB RAM | ✅ Yes |
| Docling Active | CPU OK, GPU faster | ✅ Yes |
| Flowise Active | Node server | ✅ Yes |
| GPT4All (LocalDocs) Stale (no release in 12+ months) | Desktop; CPU OK | ✅ Yes |
| h2oGPT Stale (no release in 12+ months) | GPU recommended | ✅ Yes |
| Haystack Active | Framework | ✅ Yes |
| Jan Active | Desktop; CPU/GPU (Vulkan, Metal, CUDA, ROCm). macOS: 8GB RAM for 3B, 16GB for 7B, 32GB for 13B models | ✅ Yes |
| Khoj Active | Server; GPU optional | ✅ Yes |
| KoboldCpp Active | Single binary; CPU/GPU | ✅ Yes |
| Kotaemon Active | Docker; GPU optional | ✅ Yes |
| Langflow Active | Python server | ✅ Yes |
| LibreChat No tracked release | Server + separate RAG API with pgvector | ⚠️ Needs config |
| LightRAG Active | Depends on chosen LLM; graph extraction wants a 14B+ model | ✅ Yes |
| LlamaIndex Active | Framework | ✅ Yes |
| LocalAI Active | CPU/GPU | ✅ Yes |
| LocalGPT No tracked release | GPU recommended | ✅ Yes |
| Microsoft GraphRAG Active | Indexing is LLM-heavy | ✅ Yes |
| Msty Studio No tracked release | Desktop app | ⚠️ Needs config |
| Ollama Active | CPU/GPU/Apple | ✅ Yes |
| Onyx Active | Docker; 16GB RAM suggested | ✅ Yes |
| Open Notebook Active | Docker | ✅ Yes |
| Open WebUI Active | Light server; LLM via Ollama | ✅ Yes |
| paperless-gpt Active | Needs Paperless-ngx + LLM | ✅ Yes |
| Paperless-ngx Active | Low (Raspberry Pi OK) | ✅ Yes |
| PipesHub Active | Docker stack | ✅ Yes |
| PrivateGPT Active | 8GB+ RAM; GPU recommended | ✅ Yes |
| Quivr Stale (no release in 12+ months) | Python library | ⚠️ Needs config |
| R2R Stale (no release in 12+ months) | Docker, Postgres | ⚠️ Needs config |
| RAG Web UI Active | Docker | ✅ Yes |
| RAGFlow Active | 4 cores, 16GB RAM, 50GB disk recommended (Docker) | ✅ Yes |
| Unstructured (OSS) Active | CPU; hi_res needs more | ✅ Yes |
| Verba Stale (no release in 12+ months) | Docker + Weaviate | ✅ Yes |
"Fully offline: yes" means it can run with no cloud calls once configured with local models. "Needs config" means a default (e.g. OpenAI embeddings or a cloud reranker) must be swapped out. Stale = no release in over 12 months.
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