Comparison
litgpt vs LLMmap
Verdict
Pick litgpt if litGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment; pick LLMmap if lLMmap is a Python-based tool for quick inference using pretrained models without needing additional training. It includes PyTorch weights, configuration files, and behavioral templates tailored to 52 different LLMs.
Markdown twin · litgpt alternatives · LLMmap alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | litgpt | LLMmap |
|---|---|---|
| Maintenance | Active (17d since push) As of 2w · github_public_v1 | Dormant (376d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · 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
- litgpt
- High-performance LLMs with recipes for pretraining, finetuning and deployment
- LLMmap
- Provides a ready-to-use pretrained model for open-set inference with PyTorch weights, configuration file, and behavioral templates.
Stars
- litgpt
- 14k
- LLMmap
- 405
Forks
- litgpt
- 1.5k
- LLMmap
- 46
Open issues
- litgpt
- 272
- LLMmap
- 6
Language
- litgpt
- Python
- LLMmap
- Python
Adopt for
- litgpt
- LitGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment.
- LLMmap
- LLMmap is a Python-based tool for quick inference using pretrained models without needing additional training. It includes PyTorch weights, configuration files, and behavioral templates tailored to 52 different LLMs.
Persona
- litgpt
- -
- LLMmap
- -
Runtime
- litgpt
- -
- LLMmap
- -
License
- litgpt
- LitGPT operates under the open-source Apache-2.0 license, providing permissive terms for use and modification.
- LLMmap
- MIT
Last pushed
- litgpt
- Jul 20, 2026
- LLMmap
- Jul 24, 2025
Categories
- litgpt
- Inference & Serving, LLM Frameworks, Model Training
- LLMmap
- Inference & Serving, Model Training
Trust and health
Maintenance
- litgpt
- Active (82%)
- LLMmap
- Dormant (18%)
Days since push
- litgpt
- 17d
- LLMmap
- 376d
Open issues (now)
- litgpt
- 272
- LLMmap
- 6
Stars delta
- litgpt
- +137 (30d)
- LLMmap
- Unknown
Open issues delta
- litgpt
- +6 (30d)
- LLMmap
- Unknown
Owner type
- litgpt
- Organization
- LLMmap
- User
OSV dependency advisories
- litgpt
- No lockfile (source not queried)
- LLMmap
- Published findings
Full report
- litgpt
- Trust report
- LLMmap
- Trust report
Shared compatibility
- Python · litgpt: Python runtime · LLMmap: Python runtime
Choose litgpt if…
- License: litgpt is Apache-2.0, LLMmap is MIT.
- Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models..
- Requirements: Min 16 GB RAM.
- Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large language models.
- Also covers LLM Frameworks.
- If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application.
When NOT to use litgpt
- If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources.
- When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable.
Choose LLMmap if…
- License: LLMmap is MIT, litgpt is Apache-2.0.
- Tags unique to LLMmap: open-set inference, pretrained-models, python, pytorch.
- When you need immediate model deployment and don't want or can’t afford the time to train a custom model.
When NOT to use LLMmap
- If your application requires fine-tuning on specific datasets as LLMmap offers only generic pretrained models without out-of-the-box support for further training.
- In scenarios needing advanced customization beyond the provided behavioral templates, since LLMmap’s framework might not accommodate extensive model modifications.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Lightning-AI/litgpt) · observed Aug 7, 2026
- GitHub forks (Lightning-AI/litgpt) · observed Aug 7, 2026
- Last push (Lightning-AI/litgpt) · observed Jul 20, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pasquini-dario/LLMmap) · observed Aug 5, 2026
- GitHub forks (pasquini-dario/LLMmap) · observed Aug 5, 2026
- Last push (pasquini-dario/LLMmap) · observed Jul 24, 2025
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: litgpt 14k · LLMmap 405 (synced Aug 7, 2026).
Common questions
- What is the difference between litgpt and LLMmap?
- litgpt: High-performance LLMs with recipes for pretraining, finetuning and deployment. LLMmap: Provides a ready-to-use pretrained model for open-set inference with PyTorch weights, configuration file, and behavioral templates.. See the comparison table for live GitHub stats and shared categories.
- When should I choose litgpt over LLMmap?
- Choose litgpt over LLMmap when License: litgpt is Apache-2.0, LLMmap is MIT; Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models.; Requirements: Min 16 GB RAM; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large language models; Also covers LLM Frameworks; If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application.
- When should I choose LLMmap over litgpt?
- Choose LLMmap over litgpt when License: LLMmap is MIT, litgpt is Apache-2.0; Tags unique to LLMmap: open-set inference, pretrained-models, python, pytorch; When you need immediate model deployment and don't want or can’t afford the time to train a custom model.
- When should I avoid litgpt?
- If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources. When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable.
- When should I avoid LLMmap?
- If your application requires fine-tuning on specific datasets as LLMmap offers only generic pretrained models without out-of-the-box support for further training. In scenarios needing advanced customization beyond the provided behavioral templates, since LLMmap’s framework might not accommodate extensive model modifications.
- Is litgpt or LLMmap more popular on GitHub?
- litgpt has more GitHub stars (13,605 vs 405). Stars measure visibility, not whether either tool fits your constraints.
- Are litgpt and LLMmap open source?
- Yes - both are open-source projects on GitHub (litgpt: Apache-2.0, LLMmap: MIT).
- Where can I find alternatives to litgpt or LLMmap?
- GraphCanon lists graph-backed alternatives at litgpt alternatives and LLMmap alternatives (litgpt markdown twin, LLMmap 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 LLMmap?
- litgpt: Active. LLMmap: Dormant. 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 LLMmap?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litgpt trust report; LLMmap trust report.