Home/Compare/LLMSys-PaperList vs LLMmap

Comparison

LLMSys-PaperList vs LLMmap

Verdict

Pick LLMSys-PaperList if lLMSys-PaperList offers a comprehensive list of papers and resources tailored specifically to Large Language Model (LLM) systems; 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 · LLMSys-PaperList alternatives · LLMmap alternatives

GraphCanon updated Oct 11, 2026

7views this month

LLMSys-PaperList logo

LLMSys-PaperList

AmberLJC/LLMSys-PaperList

★ 2.3kpushed Jul 25, 2026
vs
LLMmap logo

LLMmap

pasquini-dario/LLMmap

★ 469pushed Jul 24, 2025

Trust & integrity

SignalLLMSys-PaperListLLMmap
Maintenance
Steady (78d since push)
As of Oct 11, 2026 · github_public_v1
Dormant (437d since push)
As of Oct 5, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Oct 11, 2026 · github_public_v1
Not a fork · Personal account
As of Oct 5, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
Published findings
As of Jul 11, 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

LLMSys-PaperList
Curated list of academic papers related to Large Language Model systems
LLMmap
Provides a ready-to-use pretrained model for open-set inference with PyTorch weights, configuration file, and behavioral templates.

Stars

LLMSys-PaperList
2.3k
LLMmap
469

Forks

LLMSys-PaperList
123
LLMmap
51

Open issues

LLMSys-PaperList
2
LLMmap
6

Language

LLMSys-PaperList
Python
LLMmap
Python

Adopt for

LLMSys-PaperList
LLMSys-PaperList offers a comprehensive list of papers and resources tailored specifically to Large Language Model (LLM) systems.
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

LLMSys-PaperList
-
LLMmap
-

Runtime

LLMSys-PaperList
-
LLMmap
-

License

LLMSys-PaperList
(unknown)
LLMmap
MIT

Last pushed

LLMSys-PaperList
Jul 25, 2026
LLMmap
Jul 24, 2025

Categories

LLMSys-PaperList
Inference & Serving, LLM Frameworks, Model Training
LLMmap
Inference & Serving, Model Training

Trust and health

Maintenance

LLMSys-PaperList
Steady (60%)
LLMmap
Dormant (18%)

Days since push

LLMSys-PaperList
78d
LLMmap
437d

Open issues (now)

LLMSys-PaperList
2
LLMmap
6

Stars delta

LLMSys-PaperList
+51 (30d)
LLMmap
+25 (30d)

Open issues delta

LLMSys-PaperList
+1 (30d)
LLMmap
0 (30d)

OSV dependency advisories

LLMSys-PaperList
No lockfile (source not queried)
LLMmap
Published findings

Full report

LLMSys-PaperList
Trust report

Choose LLMSys-PaperList if…

  • (repository does not specify hosting environment)
  • Tags unique to LLMSys-PaperList: academic-sources, framework-overview, inference-techniques, research papers.
  • Also covers LLM Frameworks.
  • - When you need a curated list focusing on technical advancements in pre-training, post-training, serving, and multi-modal LLM systems.

When NOT to use LLMSys-PaperList

  • - If you are looking for a general repository of machine learning papers rather than specific developments related to Large Language Models.
  • - When your primary need is documentation or code examples rather than academic papers and project insights.
  • - For applications where real-time updates and active community support are imperative, as LLMSys-PaperList primarily serves as a static list without user interaction features like commenting or liveQ

Choose LLMmap if…

  • Tags unique to LLMmap: llms, open-set inference, pretrained-models, python.
  • 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 on cards: LLMSys-PaperList 2.3k · LLMmap 469 (synced Oct 11, 2026).

Common questions

What is the difference between LLMSys-PaperList and LLMmap?
LLMSys-PaperList: Curated list of academic papers related to Large Language Model systems. 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 LLMSys-PaperList over LLMmap?
Choose LLMSys-PaperList over LLMmap when (repository does not specify hosting environment); Tags unique to LLMSys-PaperList: academic-sources, framework-overview, inference-techniques, research papers; Also covers LLM Frameworks; - When you need a curated list focusing on technical advancements in pre-training, post-training, serving, and multi-modal LLM systems.
When should I choose LLMmap over LLMSys-PaperList?
Choose LLMmap over LLMSys-PaperList when Tags unique to LLMmap: llms, open-set inference, pretrained-models, python; 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 LLMSys-PaperList?
- If you are looking for a general repository of machine learning papers rather than specific developments related to Large Language Models. - When your primary need is documentation or code examples rather than academic papers and project insights. - For applications where real-time updates and active community support are imperative, as LLMSys-PaperList primarily serves as a static list without user interaction features like commenting or liveQ
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 LLMSys-PaperList or LLMmap more popular on GitHub?
LLMSys-PaperList has more GitHub stars (2,292 vs 469). Stars measure visibility, not whether either tool fits your constraints.
Are LLMSys-PaperList and LLMmap open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to LLMSys-PaperList or LLMmap?
GraphCanon lists graph-backed alternatives at LLMSys-PaperList alternatives and LLMmap alternatives (LLMSys-PaperList 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, LLMSys-PaperList or LLMmap?
LLMSys-PaperList: Steady. 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 LLMSys-PaperList and LLMmap?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLMSys-PaperList trust report; LLMmap trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.