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Comparison

litgpt vs TensorRT-LLM

Verdict

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; pick TensorRT-LLM if tensorRT-LLM is a Python API for defining and optimizing Large Language Models for efficient inference on NVIDIA GPUs, offering components for creating Python and C++ runtimes for performant inference.

Markdown twin · litgpt alternatives · TensorRT-LLM alternatives

GraphCanon updated Sep 20, 2026

12views this month

litgpt logo

litgpt

Lightning-AI/litgpt

★ 14kpushed Sep 14, 2026
vs
TensorRT-LLM logo

TensorRT-LLM

NVIDIA/TensorRT-LLM

★ 15kpushed Sep 18, 2026

Trust & integrity

SignallitgptTensorRT-LLM
Maintenance
Very active (3d since push)
As of Sep 18, 2026 · github_public_v1
Very active (0d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 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 Sep 18, 2026 · osv@v1
Published findings
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
litgpt trust reportTensorRT-LLM trust reportTrust methodology

Tagline

litgpt
High-performance LLMs for pretraining, finetuning, and deployment
TensorRT-LLM
Python API for defining and optimizing Large Language Models for efficient inference on NVIDIA GPUs

Stars

litgpt
14k
TensorRT-LLM
15k

Forks

litgpt
1.5k
TensorRT-LLM
2.8k

Open issues

litgpt
290
TensorRT-LLM
1.5k

Language

litgpt
Python
TensorRT-LLM
Python

Adopt for

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.
TensorRT-LLM
TensorRT-LLM is a Python API for defining and optimizing Large Language Models for efficient inference on NVIDIA GPUs, offering components for creating Python and C++ runtimes for performant inference execution.

Persona

litgpt
-
TensorRT-LLM
-

Runtime

litgpt
-
TensorRT-LLM
-

License

litgpt
Apache-2.0
TensorRT-LLM
Other

Last pushed

litgpt
Sep 14, 2026
TensorRT-LLM
Sep 18, 2026

Categories

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

Trust and health

Days since push

litgpt
3d
TensorRT-LLM
0d

Open issues (now)

litgpt
290
TensorRT-LLM
1.5k

Stars delta

litgpt
+62 (30d)
TensorRT-LLM
+328 (30d)

Open issues delta

litgpt
+18 (30d)
TensorRT-LLM
-106 (30d)

OSV dependency advisories

litgpt
No lockfile (source not queried)
TensorRT-LLM
Published findings

Full report

litgpt
Trust report
TensorRT-LLM
Trust report

Choose litgpt if…

  • License: litgpt is Apache-2.0, TensorRT-LLM is Other.
  • Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models.
  • Also covers LLM Frameworks.
  • 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.
GitHubDetails

Choose TensorRT-LLM if…

  • License: TensorRT-LLM is Other, litgpt is Apache-2.0.
  • Tags unique to TensorRT-LLM: blackwell, cuda, llm-serving, moe.
  • When you need to optimize Large Language Models for efficient inference on NVIDIA GPUs.

When NOT to use TensorRT-LLM

  • If your hardware does not include NVIDIA GPUs, as TensorRT-LLM is specifically optimized for NVIDIA GPUs.
  • If you do not require a Python API for defining and optimizing LLMs, and prefer a different interface or tool.
  • When you are working in a non-NVIDIA GPU environment, as TensorRT-LLM's optimizations are tailored to NVIDIA hardware.
GitHubDetails

Explore

litgpt trust report →TensorRT-LLM trust report →Inference & Serving category →LLM Frameworks category →Model Training 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: litgpt 14k · TensorRT-LLM 15k (synced Sep 20, 2026).

Common questions

What is the difference between litgpt and TensorRT-LLM?
litgpt: High-performance LLMs for pretraining, finetuning, and deployment. TensorRT-LLM: Python API for defining and optimizing Large Language Models for efficient inference on NVIDIA GPUs. See the comparison table for live GitHub stats and shared categories.
When should I choose litgpt over TensorRT-LLM?
Choose litgpt over TensorRT-LLM when License: litgpt is Apache-2.0, TensorRT-LLM is Other; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models; Also covers LLM Frameworks; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
When should I choose TensorRT-LLM over litgpt?
Choose TensorRT-LLM over litgpt when License: TensorRT-LLM is Other, litgpt is Apache-2.0; Tags unique to TensorRT-LLM: blackwell, cuda, llm-serving, moe; When you need to optimize Large Language Models for efficient inference on NVIDIA GPUs.
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.
When should I avoid TensorRT-LLM?
If your hardware does not include NVIDIA GPUs, as TensorRT-LLM is specifically optimized for NVIDIA GPUs. If you do not require a Python API for defining and optimizing LLMs, and prefer a different interface or tool. When you are working in a non-NVIDIA GPU environment, as TensorRT-LLM's optimizations are tailored to NVIDIA hardware.
Is litgpt or TensorRT-LLM more popular on GitHub?
TensorRT-LLM has more GitHub stars (14,645 vs 13,667). Stars measure visibility, not whether either tool fits your constraints.
Are litgpt and TensorRT-LLM open source?
Yes - both are open-source projects on GitHub (litgpt: Apache-2.0, TensorRT-LLM: Other).
Where can I find alternatives to litgpt or TensorRT-LLM?
GraphCanon lists graph-backed alternatives at litgpt alternatives and TensorRT-LLM alternatives (litgpt markdown twin, TensorRT-LLM 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, litgpt or TensorRT-LLM?
litgpt: Very active. TensorRT-LLM: 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 litgpt and TensorRT-LLM?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litgpt trust report; TensorRT-LLM trust report.

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