Home/Compare/Fun-ASR vs LlamaFactory

Comparison

Fun-ASR vs LlamaFactory

Verdict

Pick Fun-ASR when fun-ASR is primarily C; LlamaFactory is Python; pick LlamaFactory when llamaFactory is primarily Python; Fun-ASR is C.

Markdown twin · Fun-ASR alternatives · LlamaFactory alternatives

GraphCanon updated today

Fun-ASR logo

Fun-ASR

FunAudioLLM/Fun-ASR

1.4kpushed Jul 7, 2026
vs
LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

73kpushed Jul 10, 2026

Trust & integrity

SignalFun-ASRLlamaFactory
Maintenance
Very active (4d 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)
26 low (26 low)
As of today · osv@v1
No lockfile
As of today · none

Tagline

Fun-ASR
Fun-ASR-Nano LLM-ASR model: 31 languages, dialects, accents, lyrics, hotwords, timestamps, and speaker diarization.
LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs

Stars

Fun-ASR
1.4k
LlamaFactory
73k

Forks

Fun-ASR
136
LlamaFactory
8.9k

Open issues

Fun-ASR
0
LlamaFactory
1.1k

Language

Fun-ASR
C
LlamaFactory
Python

Adopt for

Fun-ASR
-
LlamaFactory
LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.

Persona

Fun-ASR
-
LlamaFactory
-

Runtime

Fun-ASR
-
LlamaFactory
-

License

Fun-ASR
Apache-2.0
LlamaFactory
Apache-2.0

Last pushed

Fun-ASR
Jul 7, 2026
LlamaFactory
Jul 10, 2026

Categories

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

Trust and health

Days since push

Fun-ASR
4d
LlamaFactory
0d

Open issues (now)

Fun-ASR
0
LlamaFactory
1.1k

Owner type

Fun-ASR
Organization
LlamaFactory
User

Security scan

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

Full report

LlamaFactory
Trust report

Choose Fun-ASR if…

  • Fun-ASR is primarily C; LlamaFactory is Python.
  • Tags unique to Fun-ASR: asr, audio-language-model, fun-asr, audio.
  • Also covers Inference & Serving.

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.

Choose LlamaFactory if…

  • LlamaFactory is primarily Python; Fun-ASR is C.
  • Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai.
  • When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.

When NOT to use LlamaFactory

  • When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
  • If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa

Explore

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 · LlamaFactory 73k (synced Jul 11, 2026).

Common questions

What is the difference between Fun-ASR and LlamaFactory?
Fun-ASR: Fun-ASR-Nano LLM-ASR model: 31 languages, dialects, accents, lyrics, hotwords, timestamps, and speaker diarization.. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose Fun-ASR over LlamaFactory?
Choose Fun-ASR over LlamaFactory when Fun-ASR is primarily C; LlamaFactory is Python; Tags unique to Fun-ASR: asr, audio-language-model, fun-asr, audio; Also covers Inference & Serving.
When should I choose LlamaFactory over Fun-ASR?
Choose LlamaFactory over Fun-ASR when LlamaFactory is primarily Python; Fun-ASR is C; Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
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 LlamaFactory?
When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
Is Fun-ASR or LlamaFactory more popular on GitHub?
LlamaFactory has more GitHub stars (73,157 vs 1,381). Stars measure visibility, not whether either tool fits your constraints.
Are Fun-ASR and LlamaFactory open source?
Yes - both are open-source projects on GitHub (Fun-ASR: Apache-2.0, LlamaFactory: Apache-2.0).
Where can I find alternatives to Fun-ASR or LlamaFactory?
GraphCanon lists graph-backed alternatives at Fun-ASR alternatives and LlamaFactory alternatives (Fun-ASR markdown twin, LlamaFactory 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 LlamaFactory?
Fun-ASR: Very active. LlamaFactory: 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 Fun-ASR and LlamaFactory?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Fun-ASR trust report; LlamaFactory trust report.