Comparison
paperless-gpt vs deep-searcher
Verdict
Pick paperless-gpt if paperless-gpt uses LLMs and OCR for document processing within the paperless-ngx framework, available in Go with MIT license; pick deep-searcher if deepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license.
Markdown twin · paperless-gpt alternatives · deep-searcher alternatives
GraphCanon updated Sep 19, 2026
10views this month
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Trust & integrity
| Signal | paperless-gpt | deep-searcher |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 19, 2026 · github_public_v1 | Slowing (272d since push) As of Aug 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 19, 2026 · github_public_v1 | Not a fork · Organization account As of Aug 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- paperless-gpt
- Document Digitalization powered by AI
- deep-searcher
- Open Source Deep Research Alternative to Reason and Search on Private Data.
Stars
- paperless-gpt
- 2.7k
- deep-searcher
- 8.1k
Forks
- paperless-gpt
- 208
- deep-searcher
- 775
Open issues
- paperless-gpt
- 157
- deep-searcher
- 53
Language
- paperless-gpt
- Go
- deep-searcher
- Python
Adopt for
- paperless-gpt
- paperless-gpt uses LLMs and OCR for document processing within the paperless-ngx framework, available in Go with MIT license.
- deep-searcher
- DeepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license.
Persona
- paperless-gpt
- -
- deep-searcher
- -
Runtime
- paperless-gpt
- -
- deep-searcher
- -
License
- paperless-gpt
- MIT
- deep-searcher
- Apache-2.0
Last pushed
- paperless-gpt
- Sep 19, 2026
- deep-searcher
- Nov 19, 2025
Categories
- paperless-gpt
- Computer Vision, LLM Frameworks
- deep-searcher
- AI Agents, LLM Frameworks, Vector Databases
Trust and health
Maintenance
- paperless-gpt
- Very active (96%)
- deep-searcher
- Slowing (36%)
Days since push
- paperless-gpt
- 0d
- deep-searcher
- 272d
Open issues (now)
- paperless-gpt
- 157
- deep-searcher
- 53
Stars delta
- paperless-gpt
- +87 (30d)
- deep-searcher
- +59 (30d)
Open issues delta
- paperless-gpt
- -20 (30d)
- deep-searcher
- 0 (30d)
Owner type
- paperless-gpt
- User
- deep-searcher
- Organization
OSV dependency advisories
- paperless-gpt
- Published findings
- deep-searcher
- No lockfile (source not queried)
Full report
- paperless-gpt
- Trust report
- deep-searcher
- Trust report
Choose paperless-gpt if…
- paperless-gpt is primarily Go; deep-searcher is Python.
- License: paperless-gpt is MIT, deep-searcher is Apache-2.0.
- Tags unique to paperless-gpt: ai, document-processing, ocr.
- Also covers Computer Vision.
- Need integration with existing paperless-ngx setup
When NOT to use paperless-gpt
- Looking for a tool that operates independently of paperless-ngx infrastructure
- Prefer solutions not requiring configuration for different LLM providers
- Require real-time high-volume processing where additional latency from AI integration is undesirable
Choose deep-searcher if…
- deep-searcher is primarily Python; paperless-gpt is Go.
- License: deep-searcher is Apache-2.0, paperless-gpt is MIT.
- Tags unique to deep-searcher: agent, agentic-rag, deep-research, vector-database.
- Also covers AI Agents, Vector Databases.
- When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3.
When NOT to use deep-searcher
- Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems.
- Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (icereed/paperless-gpt) · observed Sep 19, 2026
- GitHub forks (icereed/paperless-gpt) · observed Sep 19, 2026
- Last push (icereed/paperless-gpt) · observed Sep 19, 2026
- License file (MIT) · observed Sep 19, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (zilliztech/deep-searcher) · observed Sep 19, 2026
- GitHub forks (zilliztech/deep-searcher) · observed Sep 19, 2026
- Last push (zilliztech/deep-searcher) · observed Nov 19, 2025
- License file (Apache-2.0) · observed Sep 19, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: paperless-gpt 2.7k · deep-searcher 8.1k (synced Sep 19, 2026).
Common questions
- What is the difference between paperless-gpt and deep-searcher?
- paperless-gpt: Document Digitalization powered by AI. deep-searcher: Open Source Deep Research Alternative to Reason and Search on Private Data.. See the comparison table for live GitHub stats and shared categories.
- When should I choose paperless-gpt over deep-searcher?
- Choose paperless-gpt over deep-searcher when paperless-gpt is primarily Go; deep-searcher is Python; License: paperless-gpt is MIT, deep-searcher is Apache-2.0; Tags unique to paperless-gpt: ai, document-processing, ocr; Also covers Computer Vision; Need integration with existing paperless-ngx setup.
- When should I choose deep-searcher over paperless-gpt?
- Choose deep-searcher over paperless-gpt when deep-searcher is primarily Python; paperless-gpt is Go; License: deep-searcher is Apache-2.0, paperless-gpt is MIT; Tags unique to deep-searcher: agent, agentic-rag, deep-research, vector-database; Also covers AI Agents, Vector Databases; When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3.
- When should I avoid paperless-gpt?
- Looking for a tool that operates independently of paperless-ngx infrastructure Prefer solutions not requiring configuration for different LLM providers Require real-time high-volume processing where additional latency from AI integration is undesirable
- When should I avoid deep-searcher?
- Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems. Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily.
- Is paperless-gpt or deep-searcher more popular on GitHub?
- deep-searcher has more GitHub stars (8,060 vs 2,701). Stars measure visibility, not whether either tool fits your constraints.
- Are paperless-gpt and deep-searcher open source?
- Yes - both are open-source projects on GitHub (paperless-gpt: MIT, deep-searcher: Apache-2.0).
- Where can I find alternatives to paperless-gpt or deep-searcher?
- GraphCanon lists graph-backed alternatives at paperless-gpt alternatives and deep-searcher alternatives (paperless-gpt markdown twin, deep-searcher markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, paperless-gpt or deep-searcher?
- paperless-gpt: Very active. deep-searcher: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for paperless-gpt and deep-searcher?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: paperless-gpt trust report; deep-searcher trust report.