Home/Compare/dolly vs gpt4all

Comparison

dolly vs gpt4all

Verdict

Pick dolly when dolly is primarily Python; gpt4all is C++; pick gpt4all when gpt4all is primarily C++; dolly is Python.

Markdown twin · dolly alternatives · gpt4all alternatives

GraphCanon updated today

dolly logo

dolly

databrickslabs/dolly

11kpushed Jun 30, 2023
vs
gpt4all logo

gpt4all

nomic-ai/gpt4all

77kpushed May 27, 2025

Trust & integrity

Signaldollygpt4all
Maintenance
Dormant (1107d since push)
As of today · github_public_v1
Dormant (409d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
69 low (69 low)
As of today · osv@v1
No lockfile
As of today · none

Tagline

dolly
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
gpt4all
Run Local LLMs on Any Device

Stars

dolly
11k
gpt4all
77k

Forks

dolly
1.1k
gpt4all
8.3k

Open issues

dolly
6
gpt4all
768

Language

dolly
Python
gpt4all
C++

Adopt for

dolly
-
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++.

Persona

dolly
-
gpt4all
-

Runtime

dolly
-
gpt4all
-

License

dolly
Apache-2.0
gpt4all
MIT

Last pushed

dolly
Jun 30, 2023
gpt4all
May 27, 2025

Categories

dolly
Inference & Serving, LLM Frameworks, Model Training
gpt4all
Inference & Serving, LLM Frameworks

Trust and health

Days since push

dolly
1107d
gpt4all
409d

Open issues (now)

dolly
6
gpt4all
768

Security scan

dolly
69 low (69 low)
gpt4all
No lockfile

Full report

Choose dolly if…

  • dolly is primarily Python; gpt4all is C++.
  • License: dolly is Apache-2.0, gpt4all is MIT.
  • Tags unique to dolly: chatbot, databricks, dolly, gpt.
  • Also covers Model Training.

When NOT to use dolly

  • Last GitHub push was 1107 days ago (dormant maintenance, Jun 30, 2023). Validate activity before betting a new project on dolly.
  • 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.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Choose gpt4all if…

  • gpt4all is primarily C++; dolly is Python.
  • License: gpt4all is MIT, dolly is Apache-2.0.
  • 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: dolly 11k · gpt4all 77k (synced Jul 11, 2026).

Common questions

What is the difference between dolly and gpt4all?
dolly: Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform. gpt4all: Run Local LLMs on Any Device. See the comparison table for live GitHub stats and shared categories.
When should I choose dolly over gpt4all?
Choose dolly over gpt4all when dolly is primarily Python; gpt4all is C++; License: dolly is Apache-2.0, gpt4all is MIT; Tags unique to dolly: chatbot, databricks, dolly, gpt; Also covers Model Training.
When should I choose gpt4all over dolly?
Choose gpt4all over dolly when gpt4all is primarily C++; dolly is Python; License: gpt4all is MIT, dolly is Apache-2.0; Tags unique to gpt4all: ai-chat, llm-inference; - When you require on-device inference capabilities without reliance on cloud services.
When should I avoid dolly?
Last GitHub push was 1107 days ago (dormant maintenance, Jun 30, 2023). Validate activity before betting a new project on dolly. 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. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
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.
Is dolly or gpt4all more popular on GitHub?
gpt4all has more GitHub stars (77,386 vs 10,802). Stars measure visibility, not whether either tool fits your constraints.
Are dolly and gpt4all open source?
Yes - both are open-source projects on GitHub (dolly: Apache-2.0, gpt4all: MIT).
Where can I find alternatives to dolly or gpt4all?
GraphCanon lists graph-backed alternatives at dolly alternatives and gpt4all alternatives (dolly markdown twin, gpt4all 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, dolly or gpt4all?
dolly: Dormant. gpt4all: Dormant. 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 dolly and gpt4all?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dolly trust report; gpt4all trust report.