DoclingvsOpenJarvis

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

Docling

Data & ETL

IBM's document conversion tool for AI pipelines

Full review →Website ↗

OpenJarvis

AI Agent Frameworks

Local-first personal AI agents that run with Ollama

Full review →Website ↗
FeatureDoclingOpenJarvis
CategoryData & ETLAI Agent Frameworks
PricingFree (open-source)Free (open-source)
GitHub Stars
✓ More stars
15k
5k
PlatformsLinux, macOS, WindowsmacOS, Linux, Windows, WSL2, Docker
Key Features
  • ✓ PDF conversion
  • ✓ Table extraction
  • ✓ OCR
  • ✓ Markdown output
  • ✓ LlamaIndex integration
  • ✓ Local-first personal AI agents
  • ✓ Built-in Ollama support
  • ✓ Morning briefing preset
  • ✓ Deep research across web and local documents
  • ✓ Code assistant preset
  • ✓ Local engines: Ollama, vLLM, SGLang, llama.cpp
  • ✓ Optional cloud engines
  • ✓ Energy, cost and latency-aware routing
Pros
  • + Excellent PDF parsing
  • + Table extraction
  • + OCR capability
  • + IBM Research quality
  • + LlamaIndex integration
  • + Strong fit for Ollama-based local agent workflows
  • + Apache-2.0 open-source project
  • + Ships ready-to-run presets instead of only framework primitives
  • + Supports both local engines and optional cloud escalation
  • + Built around privacy, cost, latency and energy as first-class constraints
Cons
  • − Heavy dependencies
  • − Can be slow on large docs
  • − Python only
  • − Complex output format
  • − Young v1.0 project with fast-moving docs and releases
  • − Local-first does not mean cloud-free unless configured that way
  • − Personal-agent presets may need access to sensitive local files, email or calendar data
  • − Efficiency claims are project-reported and should be tested on your own workloads
Tags
documentspdfconversionibm
open-sourcelocal-firstpersonal-aiagentsollamalocal-airesearchpython

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