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Home/Compare/LlamaFactory vs surogate

Comparison

LlamaFactory vs surogate

Verdict

Pick LlamaFactory when llamaFactory is primarily Python; surogate is C++; pick surogate when surogate is primarily C++; LlamaFactory is Python.

Markdown twin · LlamaFactory alternatives · surogate alternatives

GraphCanon updated today

LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

★ 73kpushed Jul 10, 2026
vs
surogate logo

surogate

invergent-ai/surogate

★ 806pushed Jul 7, 2026

Trust & integrity

SignalLlamaFactorysurogate
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (4d 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 lockfile
As of today · none
LlamaFactory trust reportsurogate trust reportTrust methodology

Tagline

LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
surogate
Training/Fine-tuning at the speed of light

Stars

LlamaFactory
73k
surogate
806

Forks

LlamaFactory
8.9k
surogate
6

Open issues

LlamaFactory
1.1k
surogate
7

Language

LlamaFactory
Python
surogate
C++

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.
surogate
-

Persona

LlamaFactory
-
surogate
-

Runtime

LlamaFactory
-
surogate
-

License

LlamaFactory
Apache-2.0
surogate
Apache-2.0

Last pushed

LlamaFactory
Jul 10, 2026
surogate
Jul 7, 2026

Categories

LlamaFactory
Model Training, LLM Frameworks
surogate
LLM Frameworks, Model Training

Trust and health

Days since push

LlamaFactory
0d
surogate
4d

Open issues (now)

LlamaFactory
1.1k
surogate
7

Owner type

LlamaFactory
User
surogate
Organization

Full report

LlamaFactory
Trust report
surogate
Trust report

Choose LlamaFactory if…

  • LlamaFactory is primarily Python; surogate is C++.
  • Tags unique to LlamaFactory: gemma, deepseek, ai, instruction-tuning.
  • 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
GitHubDetails

Choose surogate if…

  • surogate is primarily C++; LlamaFactory is Python.
  • Tags unique to surogate: llms, llama, deep-learning, llm.
  • Leaner open-issue backlog (7).

When NOT to use surogate

  • 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.
GitHubDetails

Explore

LlamaFactory trust report →surogate trust report →Model Training category →LLM Frameworks 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: LlamaFactory 73k · surogate 806 (synced Jul 11, 2026).

Common questions

What is the difference between LlamaFactory and surogate?
LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. surogate: Training/Fine-tuning at the speed of light. See the comparison table for live GitHub stats and shared categories.
When should I choose LlamaFactory over surogate?
Choose LlamaFactory over surogate when LlamaFactory is primarily Python; surogate is C++; Tags unique to LlamaFactory: gemma, deepseek, ai, instruction-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
When should I choose surogate over LlamaFactory?
Choose surogate over LlamaFactory when surogate is primarily C++; LlamaFactory is Python; Tags unique to surogate: llms, llama, deep-learning, llm; Leaner open-issue backlog (7).
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 surogate?
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.
Is LlamaFactory or surogate more popular on GitHub?
LlamaFactory has more GitHub stars (73,157 vs 806). Stars measure visibility, not whether either tool fits your constraints.
Are LlamaFactory and surogate open source?
Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, surogate: Apache-2.0).
Where can I find alternatives to LlamaFactory or surogate?
GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and surogate alternatives (LlamaFactory markdown twin, surogate 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 surogate?
LlamaFactory: Very active. surogate: 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 surogate?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; surogate trust report.