Comparison
gpt4all vs LLM-Hub
Verdict
Pick gpt4all when license: gpt4all is MIT, LLM-Hub is Other; pick LLM-Hub when license: LLM-Hub is Other, gpt4all is MIT.
Markdown twin · gpt4all alternatives · LLM-Hub alternatives
GraphCanon updated today
Trust & integrity
| Signal | gpt4all | LLM-Hub |
|---|---|---|
| Maintenance | Dormant (409d since push) As of today · github_public_v1 | Very active (0d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- gpt4all
- Run Local LLMs on Any Device
- LLM-Hub
- Local AI Assistant on your phone
Stars
- gpt4all
- 77k
- LLM-Hub
- 491
Forks
- gpt4all
- 8.3k
- LLM-Hub
- 103
Open issues
- gpt4all
- 768
- LLM-Hub
- 31
Language
- gpt4all
- C++
- LLM-Hub
- C++
Adopt for
- gpt4all
- GPT4All is an open-source project designed to facilitate the local deployment of large language models (LLMs). It supports commercial usage with a permissive MIT license and is implemented in C++.
- LLM-Hub
- -
Persona
- gpt4all
- -
- LLM-Hub
- -
Runtime
- gpt4all
- -
- LLM-Hub
- -
License
- gpt4all
- MIT
- LLM-Hub
- Other
Last pushed
- gpt4all
- May 27, 2025
- LLM-Hub
- Jul 11, 2026
Categories
- gpt4all
- Inference & Serving, LLM Frameworks
- LLM-Hub
- AI Agents, Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- gpt4all
- Dormant (18%)
- LLM-Hub
- Very active (96%)
Days since push
- gpt4all
- 409d
- LLM-Hub
- 0d
Open issues (now)
- gpt4all
- 768
- LLM-Hub
- 31
Owner type
- gpt4all
- Organization
- LLM-Hub
- User
Full report
- gpt4all
- Trust report
- LLM-Hub
- Trust report
Choose gpt4all if…
- License: gpt4all is MIT, LLM-Hub is Other.
- Tags unique to gpt4all: ai-chat, llm-inference.
- - When you require on-device inference capabilities without reliance on cloud services.
When NOT to use gpt4all
- - In environments strictly requiring models supported by mainstream frameworks like TensorFlow or PyTorch, as GPT4All focuses on its standalone implementation.
- - When the project demands seamless integration with popular cloud infrastructures that don't align well with local deployments.
Choose LLM-Hub if…
- License: LLM-Hub is Other, gpt4all is MIT.
- Tags unique to LLM-Hub: ai, gemma3, gemma3n, gemma4.
- Also covers AI Agents.
When NOT to use LLM-Hub
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (nomic-ai/gpt4all) · observed Jul 11, 2026
- GitHub forks (nomic-ai/gpt4all) · observed Jul 11, 2026
- Last push (nomic-ai/gpt4all) · observed May 27, 2025
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (timmyy123/LLM-Hub) · observed Jul 11, 2026
- GitHub forks (timmyy123/LLM-Hub) · observed Jul 11, 2026
- Last push (timmyy123/LLM-Hub) · observed Jul 11, 2026
- License file (Other) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt4all 77k · LLM-Hub 491 (synced Jul 11, 2026).
Common questions
- What is the difference between gpt4all and LLM-Hub?
- gpt4all: Run Local LLMs on Any Device. LLM-Hub: Local AI Assistant on your phone. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt4all over LLM-Hub?
- Choose gpt4all over LLM-Hub when License: gpt4all is MIT, LLM-Hub is Other; Tags unique to gpt4all: ai-chat, llm-inference; - When you require on-device inference capabilities without reliance on cloud services.
- When should I choose LLM-Hub over gpt4all?
- Choose LLM-Hub over gpt4all when License: LLM-Hub is Other, gpt4all is MIT; Tags unique to LLM-Hub: ai, gemma3, gemma3n, gemma4; Also covers AI Agents.
- When should I avoid gpt4all?
- - In environments strictly requiring models supported by mainstream frameworks like TensorFlow or PyTorch, as GPT4All focuses on its standalone implementation. - When the project demands seamless integration with popular cloud infrastructures that don't align well with local deployments.
- When should I avoid LLM-Hub?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Is gpt4all or LLM-Hub more popular on GitHub?
- gpt4all has more GitHub stars (77,386 vs 491). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt4all and LLM-Hub open source?
- Yes - both are open-source projects on GitHub (gpt4all: MIT, LLM-Hub: Other).
- Where can I find alternatives to gpt4all or LLM-Hub?
- GraphCanon lists graph-backed alternatives at gpt4all alternatives and LLM-Hub alternatives (gpt4all markdown twin, LLM-Hub 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, gpt4all or LLM-Hub?
- gpt4all: Dormant. LLM-Hub: 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 gpt4all and LLM-Hub?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt4all trust report; LLM-Hub trust report.