Home/Compare/LlamaFactory vs FunASR

Comparison

LlamaFactory vs FunASR

Verdict

Pick LlamaFactory when license: LlamaFactory is Apache-2.0, FunASR is MIT; pick FunASR when license: FunASR is MIT, LlamaFactory is Apache-2.0.

Markdown twin · LlamaFactory alternatives · FunASR alternatives

GraphCanon updated today

LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

73kpushed Jul 10, 2026
vs
FunASR logo

FunASR

modelscope/FunASR

19kpushed Jul 10, 2026

Trust & integrity

SignalLlamaFactoryFunASR
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (1d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No criticals
As of today · mcp_manifest@v1

Tagline

LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
FunASR
Industrial-grade speech recognition toolkit: 170x realtime, 50+ languages, speaker diarization, emotion detection, streaming, and OpenAI-compatible API.

Stars

LlamaFactory
73k
FunASR
19k

Forks

LlamaFactory
8.9k
FunASR
1.9k

Open issues

LlamaFactory
1.1k
FunASR
1

Language

LlamaFactory
Python
FunASR
Python

Adopt for

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.
FunASR
-

Persona

LlamaFactory
-
FunASR
-

Runtime

LlamaFactory
-
FunASR
-

License

LlamaFactory
Apache-2.0
FunASR
MIT

Last pushed

LlamaFactory
Jul 10, 2026
FunASR
Jul 10, 2026

Categories

LlamaFactory
LLM Frameworks, Model Training
FunASR
LLM Frameworks, Model Training, Inference & Serving

Trust and health

Days since push

LlamaFactory
0d
FunASR
1d

Open issues (now)

LlamaFactory
1.1k
FunASR
1

Owner type

LlamaFactory
User
FunASR
Organization

Security scan

LlamaFactory
No lockfile
FunASR
No criticals

Full report

LlamaFactory
Trust report

Choose LlamaFactory if…

  • License: LlamaFactory is Apache-2.0, FunASR is MIT.
  • 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

Choose FunASR if…

  • License: FunASR is MIT, LlamaFactory is Apache-2.0.
  • Tags unique to FunASR: mcp-server, asr, chinese, multilingual-asr.
  • Also covers Inference & Serving.

When NOT to use FunASR

  • 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.

Explore

Sources

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

GitHub stars on cards: LlamaFactory 73k · FunASR 19k (synced Jul 11, 2026).

Common questions

What is the difference between LlamaFactory and FunASR?
LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. FunASR: Industrial-grade speech recognition toolkit: 170x realtime, 50+ languages, speaker diarization, emotion detection, streaming, and OpenAI-compatible API.. See the comparison table for live GitHub stats and shared categories.
When should I choose LlamaFactory over FunASR?
Choose LlamaFactory over FunASR when License: LlamaFactory is Apache-2.0, FunASR is MIT; 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 choose FunASR over LlamaFactory?
Choose FunASR over LlamaFactory when License: FunASR is MIT, LlamaFactory is Apache-2.0; Tags unique to FunASR: mcp-server, asr, chinese, multilingual-asr; Also covers Inference & Serving.
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
When should I avoid FunASR?
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.
Is LlamaFactory or FunASR more popular on GitHub?
LlamaFactory has more GitHub stars (73,157 vs 19,141). Stars measure visibility, not whether either tool fits your constraints.
Are LlamaFactory and FunASR open source?
Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, FunASR: MIT).
Where can I find alternatives to LlamaFactory or FunASR?
GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and FunASR alternatives (LlamaFactory markdown twin, FunASR 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, LlamaFactory or FunASR?
LlamaFactory: Very active. FunASR: 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 LlamaFactory and FunASR?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; FunASR trust report.