Comparison
hypersigil vs private-gpt
Verdict
Pick hypersigil if hypersigil is a prompt management gateway with a user interface designed for non-technical users to test, refine, and deploy prompts across multiple AI providers; pick private-gpt if privateGPT provides a comprehensive API layer to build private, on-premise AI applications leveraging local OpenAI-compatible inference servers. It offers features such as RAG, skills, tools, text-to-SQL functionalities,.
Markdown twin · hypersigil alternatives · private-gpt alternatives
GraphCanon updated Sep 20, 2026
17views this month
vs
Trust & integrity
| Signal | hypersigil | private-gpt |
|---|---|---|
| Maintenance | Slowing (153d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 8, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 8, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 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
- hypersigil
- Prompt management gateway with UI for AI applications
- private-gpt
- Complete API layer for private AI applications on local models
Stars
- hypersigil
- 28
- private-gpt
- 57k
Forks
- hypersigil
- 2
- private-gpt
- 7.6k
Open issues
- hypersigil
- 0
- private-gpt
- 8
Language
- hypersigil
- Vue
- private-gpt
- Python
Adopt for
- hypersigil
- Hypersigil is a prompt management gateway with a user interface designed for non-technical users to test, refine, and deploy prompts across multiple AI providers.
- private-gpt
- PrivateGPT provides a comprehensive API layer to build private, on-premise AI applications leveraging local OpenAI-compatible inference servers. It offers features such as RAG, skills, tools, text-to-SQL functionalities,
Persona
- hypersigil
- -
- private-gpt
- -
Runtime
- hypersigil
- -
- private-gpt
- -
License
- hypersigil
- Hypersigil is licensed under Apache 2.0 with Commons Clause, allowing internal business use, modification, and distribution, but prohibiting commercial selling.
- private-gpt
- Apache-2.0
Last pushed
- hypersigil
- Apr 17, 2026
- private-gpt
- Sep 7, 2026
Categories
- hypersigil
- Developer Tools, Evaluation & Observability
- private-gpt
- Inference & Serving
Trust and health
Maintenance
- hypersigil
- Slowing (36%)
- private-gpt
- Very active (96%)
Days since push
- hypersigil
- 153d
- private-gpt
- 0d
Open issues (now)
- hypersigil
- 0
- private-gpt
- 8
Stars delta
- hypersigil
- +1 (30d)
- private-gpt
- +82 (30d)
Open issues delta
- hypersigil
- 0 (30d)
- private-gpt
- +5 (30d)
OSV dependency advisories
- hypersigil
- Published findings
- private-gpt
- No lockfile (source not queried)
Full report
- hypersigil
- Trust report
- private-gpt
- Trust report
Typed relationship
hypersigil alternative private-gptBoth PrivateGPT and hypersigil offer integrated solutions to manage prompts for AI applications, positioning them as alternatives.
Choose hypersigil if…
- hypersigil is primarily Vue; private-gpt is Python.
- License: hypersigil is Other, private-gpt is Apache-2.0.
- Pricing: Free to use and modify for internal purposes, but cannot be sold commercially..
- Requirements: Min 2 GB RAM; Requires Docker; Requires Docker for running the application in a containerized environment.; Needs a Vue.js frontend and a backend server to be started separately for full functionality..
- Both PrivateGPT and hypersigil offer integrated solutions to manage prompts for AI applications, positioning them as alternatives.
- Tags unique to hypersigil: llm, llm-evaluation, llm-gateway, prompt-engineering.
- Also covers Developer Tools, Evaluation & Observability.
- When you need a tool that allows non-technical users to manage prompts effectively without deep technical knowledge.
When NOT to use hypersigil
- If you are looking for a tool that can be sold commercially as a product or service, as Hypersigil's license prohibits commercial selling.
- When you require a tool that does not involve a user interface and prefers command-line operations for prompt management.
Choose private-gpt if…
- private-gpt is primarily Python; hypersigil is Vue.
- License: private-gpt is Apache-2.0, hypersigil is Other.
- Requirements: Min 8 GB RAM; Requires Docker.
- Both PrivateGPT and hypersigil offer integrated solutions to manage prompts for AI applications, positioning them as alternatives.
- Tags unique to private-gpt: ai, ai-tools, local-models, mcp.
- Also covers Inference & Serving.
- - You need to deploy and operationalize your own locally-run models without relying on cloud APIs.
When NOT to use private-gpt
- - You prefer simplicity and ease-of-use over full control; PrivateGPT requires more setup than using direct cloud-based AI services.
- - Your project does not involve running models locally but strictly relies on public cloud resources for inference server operations.
- - You do not have the technical capability to run an OpenAI-compatible inference server or manage local infrastructure effectively.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hypersigilhq/hypersigil) · observed Sep 20, 2026
- GitHub forks (hypersigilhq/hypersigil) · observed Sep 20, 2026
- Last push (hypersigilhq/hypersigil) · observed Apr 17, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (zylon-ai/private-gpt) · observed Sep 20, 2026
- GitHub forks (zylon-ai/private-gpt) · observed Sep 20, 2026
- Last push (zylon-ai/private-gpt) · observed Sep 7, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: hypersigil 28 · private-gpt 57k (synced Sep 20, 2026).
Common questions
- What is the difference between hypersigil and private-gpt?
- hypersigil: Prompt management gateway with UI for AI applications. private-gpt: Complete API layer for private AI applications on local models. See the comparison table for live GitHub stats and shared categories.
- When should I choose hypersigil over private-gpt?
- Choose hypersigil over private-gpt when hypersigil is primarily Vue; private-gpt is Python; License: hypersigil is Other, private-gpt is Apache-2.0; Pricing: Free to use and modify for internal purposes, but cannot be sold commercially.; Requirements: Min 2 GB RAM; Requires Docker; Requires Docker for running the application in a containerized environment.; Needs a Vue.js frontend and a backend server to be started separately for full functionality.; Both PrivateGPT and hypersigil offer integrated solutions to manage prompts for AI applications, positioning them as alternatives; Tags unique to hypersigil: llm, llm-evaluation, llm-gateway, prompt-engineering; Also covers Developer Tools, Evaluation & Observability; When you need a tool that allows non-technical users to manage prompts effectively without deep technical knowledge.
- When should I choose private-gpt over hypersigil?
- Choose private-gpt over hypersigil when private-gpt is primarily Python; hypersigil is Vue; License: private-gpt is Apache-2.0, hypersigil is Other; Requirements: Min 8 GB RAM; Requires Docker; Both PrivateGPT and hypersigil offer integrated solutions to manage prompts for AI applications, positioning them as alternatives; Tags unique to private-gpt: ai, ai-tools, local-models, mcp; Also covers Inference & Serving; - You need to deploy and operationalize your own locally-run models without relying on cloud APIs.
- When should I avoid hypersigil?
- If you are looking for a tool that can be sold commercially as a product or service, as Hypersigil's license prohibits commercial selling. When you require a tool that does not involve a user interface and prefers command-line operations for prompt management.
- When should I avoid private-gpt?
- - You prefer simplicity and ease-of-use over full control; PrivateGPT requires more setup than using direct cloud-based AI services. - Your project does not involve running models locally but strictly relies on public cloud resources for inference server operations. - You do not have the technical capability to run an OpenAI-compatible inference server or manage local infrastructure effectively.
- Is hypersigil or private-gpt more popular on GitHub?
- private-gpt has more GitHub stars (57,497 vs 28). Stars measure visibility, not whether either tool fits your constraints.
- Are hypersigil and private-gpt open source?
- Yes - both are open-source projects on GitHub (hypersigil: Other, private-gpt: Apache-2.0).
- Where can I find alternatives to hypersigil or private-gpt?
- GraphCanon lists graph-backed alternatives at hypersigil alternatives and private-gpt alternatives (hypersigil markdown twin, private-gpt 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, hypersigil or private-gpt?
- hypersigil: Slowing. private-gpt: Very active. 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 hypersigil and private-gpt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hypersigil trust report; private-gpt trust report.