Home/Compare/LLM-Adapters vs litgpt

Comparison

LLM-Adapters vs litgpt

Verdict

Pick LLM-Adapters if lLM-Adapters offers Python-based tools for efficient fine-tuning of language models with Apache-2.0 licensing; pick litgpt if litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license.

Markdown twin · LLM-Adapters alternatives · litgpt alternatives

GraphCanon updated Sep 20, 2026

14views this month

LLM-Adapters logo

LLM-Adapters

AGI-Edgerunners/LLM-Adapters

★ 1.2kpushed Mar 10, 2024
vs
litgpt logo

litgpt

Lightning-AI/litgpt

★ 14kpushed Sep 14, 2026

Trust & integrity

SignalLLM-Adapterslitgpt
Maintenance
Dormant (923d since push)
As of Sep 19, 2026 · github_public_v1
Very active (3d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 19, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

LLM-Adapters
Code for EMNLP 2023 Paper on Parameter-Efficient Fine-Tuning of LLMs
litgpt
High-performance LLMs for pretraining, finetuning, and deployment

Stars

LLM-Adapters
1.2k
litgpt
14k

Forks

LLM-Adapters
116
litgpt
1.5k

Open issues

LLM-Adapters
55
litgpt
290

Language

LLM-Adapters
Python
litgpt
Python

Adopt for

LLM-Adapters
LLM-Adapters offers Python-based tools for efficient fine-tuning of language models with Apache-2.0 licensing.
litgpt
litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license.

Persona

LLM-Adapters
-
litgpt
-

Runtime

LLM-Adapters
-
litgpt
-

License

LLM-Adapters
Apache-2.0
litgpt
Apache-2.0

Last pushed

LLM-Adapters
Mar 10, 2024
litgpt
Sep 14, 2026

Categories

LLM-Adapters
LLM Frameworks, Model Training
litgpt
Inference & Serving, LLM Frameworks, Model Training

Trust and health

Maintenance

LLM-Adapters
Dormant (18%)
litgpt
Very active (96%)

Days since push

LLM-Adapters
923d
litgpt
3d

Open issues (now)

LLM-Adapters
55
litgpt
290

Stars delta

LLM-Adapters
+1 (30d)
litgpt
+62 (30d)

Open issues delta

LLM-Adapters
0 (30d)
litgpt
+18 (30d)

Full report

LLM-Adapters
Trust report

Shared compatibility

  • Python · LLM-Adapters: Python runtime · litgpt: Python runtime

Choose LLM-Adapters if…

  • Tags unique to LLM-Adapters: adapters, fine-tuning, parameter-efficient.
  • Optimizing resource usage when you need to fine-tune large language models without altering their core parameters
  • Leaner open-issue backlog (55).

When NOT to use LLM-Adapters

  • You require a full retraining approach that modifies all model weights, not just adapters
  • Your project timeline does not allow for integrating and testing new methodologies from recent papers like EMNLP 2023

Choose litgpt if…

  • Tags unique to litgpt: ai, artificial-intelligence, deep-learning, llm.
  • Also covers Inference & Serving.
  • When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.

When NOT to use litgpt

  • If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based.
  • When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases.
  • If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license.

Explore

Sources

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

GitHub stars on cards: LLM-Adapters 1.2k · litgpt 14k (synced Sep 20, 2026).

Common questions

What is the difference between LLM-Adapters and litgpt?
LLM-Adapters: Code for EMNLP 2023 Paper on Parameter-Efficient Fine-Tuning of LLMs. litgpt: High-performance LLMs for pretraining, finetuning, and deployment. See the comparison table for live GitHub stats and shared categories.
When should I choose LLM-Adapters over litgpt?
Choose LLM-Adapters over litgpt when Tags unique to LLM-Adapters: adapters, fine-tuning, parameter-efficient; Optimizing resource usage when you need to fine-tune large language models without altering their core parameters; Leaner open-issue backlog (55).
When should I choose litgpt over LLM-Adapters?
Choose litgpt over LLM-Adapters when Tags unique to litgpt: ai, artificial-intelligence, deep-learning, llm; Also covers Inference & Serving; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
When should I avoid LLM-Adapters?
You require a full retraining approach that modifies all model weights, not just adapters Your project timeline does not allow for integrating and testing new methodologies from recent papers like EMNLP 2023
When should I avoid litgpt?
If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license.
Is LLM-Adapters or litgpt more popular on GitHub?
litgpt has more GitHub stars (13,667 vs 1,235). Stars measure visibility, not whether either tool fits your constraints.
Are LLM-Adapters and litgpt open source?
Yes - both are open-source projects on GitHub (LLM-Adapters: Apache-2.0, litgpt: Apache-2.0).
Where can I find alternatives to LLM-Adapters or litgpt?
GraphCanon lists graph-backed alternatives at LLM-Adapters alternatives and litgpt alternatives (LLM-Adapters markdown twin, litgpt 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, LLM-Adapters or litgpt?
LLM-Adapters: Dormant. litgpt: 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 LLM-Adapters and litgpt?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLM-Adapters trust report; litgpt trust report.

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