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Comparison

Fun-ASR vs gpt4all

Verdict

Pick Fun-ASR when fun-ASR is primarily C; gpt4all is C++; pick gpt4all when gpt4all is primarily C++; Fun-ASR is C.

Markdown twin · Fun-ASR alternatives · gpt4all alternatives

GraphCanon updated today

Fun-ASR logo

Fun-ASR

FunAudioLLM/Fun-ASR

★ 1.4kpushed Jul 7, 2026
vs
gpt4all logo

gpt4all

nomic-ai/gpt4all

★ 77kpushed May 27, 2025

Trust & integrity

SignalFun-ASRgpt4all
Maintenance
Very active (4d 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)
26 low (26 low)
As of today · osv@v1
No lockfile
As of today · none
Fun-ASR trust reportgpt4all trust reportTrust methodology

Tagline

Fun-ASR
Fun-ASR-Nano LLM-ASR model: 31 languages, dialects, accents, lyrics, hotwords, timestamps, and speaker diarization.
gpt4all
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

Stars

Fun-ASR
1.4k
gpt4all
77k

Forks

Fun-ASR
136
gpt4all
8.3k

Open issues

Fun-ASR
0
gpt4all
768

Language

Fun-ASR
C
gpt4all
C++

Adopt for

Fun-ASR
-
gpt4all
-

Persona

Fun-ASR
-
gpt4all
-

Runtime

Fun-ASR
-
gpt4all
-

License

Fun-ASR
Apache-2.0
gpt4all
MIT

Last pushed

Fun-ASR
Jul 7, 2026
gpt4all
May 27, 2025

Categories

Fun-ASR
LLM Frameworks, Model Training, Inference & Serving
gpt4all
LLM Frameworks, Inference & Serving

Trust and health

Maintenance

Fun-ASR
Very active (96%)
gpt4all
Dormant (18%)

Days since push

Fun-ASR
4d
gpt4all
409d

Open issues (now)

Fun-ASR
0
gpt4all
768

Security scan

Fun-ASR
26 low (26 low)
gpt4all
No lockfile

Full report

Fun-ASR
Trust report
gpt4all
Trust report

Choose Fun-ASR if…

  • Fun-ASR is primarily C; gpt4all is C++.
  • License: Fun-ASR is Apache-2.0, gpt4all is MIT.
  • Tags unique to Fun-ASR: asr, audio-language-model, fun-asr, audio.
  • Also covers Model Training.

When NOT to use Fun-ASR

  • 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.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
GitHubDetails

Choose gpt4all if…

  • gpt4all is primarily C++; Fun-ASR is C.
  • License: gpt4all is MIT, Fun-ASR is Apache-2.0.
  • Tags unique to gpt4all: ai-chat, c++, llm-inference.

When NOT to use gpt4all

  • Last GitHub push was 410 days ago (dormant maintenance, May 27, 2025). Validate activity before betting a new project on gpt4all.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
GitHubDetails

Explore

Fun-ASR trust report →gpt4all trust report →LLM Frameworks category →Model Training category →Inference & Serving category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: Fun-ASR 1.4k · gpt4all 77k (synced Jul 11, 2026).

Common questions

What is the difference between Fun-ASR and gpt4all?
Fun-ASR: Fun-ASR-Nano LLM-ASR model: 31 languages, dialects, accents, lyrics, hotwords, timestamps, and speaker diarization.. gpt4all: GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.. See the comparison table for live GitHub stats and shared categories.
When should I choose Fun-ASR over gpt4all?
Choose Fun-ASR over gpt4all when Fun-ASR is primarily C; gpt4all is C++; License: Fun-ASR is Apache-2.0, gpt4all is MIT; Tags unique to Fun-ASR: asr, audio-language-model, fun-asr, audio; Also covers Model Training.
When should I choose gpt4all over Fun-ASR?
Choose gpt4all over Fun-ASR when gpt4all is primarily C++; Fun-ASR is C; License: gpt4all is MIT, Fun-ASR is Apache-2.0; Tags unique to gpt4all: ai-chat, c++, llm-inference.
When should I avoid Fun-ASR?
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. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
When should I avoid gpt4all?
Last GitHub push was 410 days ago (dormant maintenance, May 27, 2025). Validate activity before betting a new project on gpt4all. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Is Fun-ASR or gpt4all more popular on GitHub?
gpt4all has more GitHub stars (77,386 vs 1,381). Stars measure visibility, not whether either tool fits your constraints.
Are Fun-ASR and gpt4all open source?
Yes - both are open-source projects on GitHub (Fun-ASR: Apache-2.0, gpt4all: MIT).
Where can I find alternatives to Fun-ASR or gpt4all?
GraphCanon lists graph-backed alternatives at Fun-ASR alternatives and gpt4all alternatives (Fun-ASR 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, Fun-ASR or gpt4all?
Fun-ASR: Very active. 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 Fun-ASR and gpt4all?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Fun-ASR trust report; gpt4all trust report.