Home/Compare/DistiLlama vs awesome-LLM-resources

Comparison

DistiLlama vs awesome-LLM-resources

Verdict

Pick DistiLlama if distiLlama is a Chrome extension for summarizing and chatting with web pages and local documents using locally running language models to ensure data privacy; pick awesome-LLM-resources if awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.

Markdown twin · DistiLlama alternatives · awesome-LLM-resources alternatives

GraphCanon updated Sep 20, 2026

10views this month

DistiLlama logo

DistiLlama

shreyaskarnik/DistiLlama

304pushed Sep 2, 2024
vs
awesome-LLM-resources logo

awesome-LLM-resources

WangRongsheng/awesome-LLM-resources

9.0kpushed Sep 14, 2026

Trust & integrity

SignalDistiLlamaawesome-LLM-resources
Maintenance
Dormant (747d since push)
As of Sep 20, 2026 · github_public_v1
Very active (3d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Sep 20, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 15, 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

DistiLlama
Chrome Extension for Summarizing and Chatting with Web Pages/Local Docs Using Local LLMs
awesome-LLM-resources
Summary of the world's best LLM resources.

Stars

DistiLlama
304
awesome-LLM-resources
9.0k

Forks

DistiLlama
32
awesome-LLM-resources
993

Open issues

DistiLlama
9
awesome-LLM-resources
40

Language

DistiLlama
TypeScript
awesome-LLM-resources
-

Adopt for

DistiLlama
DistiLlama is a Chrome extension for summarizing and chatting with web pages and local documents using locally running language models to ensure data privacy.
awesome-LLM-resources
awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.

Persona

DistiLlama
-
awesome-LLM-resources
-

Runtime

DistiLlama
-
awesome-LLM-resources
-

License

DistiLlama
MIT
awesome-LLM-resources
The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution.

Last pushed

DistiLlama
Sep 2, 2024
awesome-LLM-resources
Sep 14, 2026

Categories

DistiLlama
AI Agents, LLM Frameworks
awesome-LLM-resources
AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training

Trust and health

Maintenance

DistiLlama
Dormant (18%)
awesome-LLM-resources
Very active (96%)

Days since push

DistiLlama
747d
awesome-LLM-resources
3d

Open issues (now)

DistiLlama
9
awesome-LLM-resources
40

Stars delta

DistiLlama
0 (30d)
awesome-LLM-resources
+123 (30d)

Open issues delta

DistiLlama
0 (30d)
awesome-LLM-resources
+17 (30d)

Full report

DistiLlama
Trust report
awesome-LLM-resources
Trust report

Choose DistiLlama if…

  • License: DistiLlama is MIT, awesome-LLM-resources is Apache-2.0.
  • Pricing: DistiLlama is free and open source software under the MIT license, however, users are responsible for maintaining and running their own local language models..
  • Tags unique to DistiLlama: chrome-extension, langchain, llama2, local-llm.
  • When you prioritize data privacy and prefer not to send sensitive information over the internet for processing.

When NOT to use DistiLlama

  • If your setup does not support the execution of local language models, as this is a prerequisite for using DistiLlama effectively.
  • When you require real-time interaction or access to cloud-based resources for more dynamic content generation since local LLMs may be limited by hardware performance.

Choose awesome-LLM-resources if…

  • License: awesome-LLM-resources is Apache-2.0, DistiLlama is MIT.
  • Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs..
  • Requirements: The repository does not specify any technical requirements for accessing its content..
  • Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models.
  • Also covers Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training.
  • When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.

When NOT to use awesome-LLM-resources

  • If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider.
  • When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.

Explore

Sources

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

GitHub stars on cards: DistiLlama 304 · awesome-LLM-resources 9.0k (synced Sep 20, 2026).

Common questions

What is the difference between DistiLlama and awesome-LLM-resources?
DistiLlama: Chrome Extension for Summarizing and Chatting with Web Pages/Local Docs Using Local LLMs. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories.
When should I choose DistiLlama over awesome-LLM-resources?
Choose DistiLlama over awesome-LLM-resources when License: DistiLlama is MIT, awesome-LLM-resources is Apache-2.0; Pricing: DistiLlama is free and open source software under the MIT license, however, users are responsible for maintaining and running their own local language models.; Tags unique to DistiLlama: chrome-extension, langchain, llama2, local-llm; When you prioritize data privacy and prefer not to send sensitive information over the internet for processing.
When should I choose awesome-LLM-resources over DistiLlama?
Choose awesome-LLM-resources over DistiLlama when License: awesome-LLM-resources is Apache-2.0, DistiLlama is MIT; Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.; Requirements: The repository does not specify any technical requirements for accessing its content.; Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models; Also covers Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training; When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.
When should I avoid DistiLlama?
If your setup does not support the execution of local language models, as this is a prerequisite for using DistiLlama effectively. When you require real-time interaction or access to cloud-based resources for more dynamic content generation since local LLMs may be limited by hardware performance.
When should I avoid awesome-LLM-resources?
If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.
Is DistiLlama or awesome-LLM-resources more popular on GitHub?
awesome-LLM-resources has more GitHub stars (8,968 vs 304). Stars measure visibility, not whether either tool fits your constraints.
Are DistiLlama and awesome-LLM-resources open source?
Yes - both are open-source projects on GitHub (DistiLlama: MIT, awesome-LLM-resources: Apache-2.0).
Where can I find alternatives to DistiLlama or awesome-LLM-resources?
GraphCanon lists graph-backed alternatives at DistiLlama alternatives and awesome-LLM-resources alternatives (DistiLlama markdown twin, awesome-LLM-resources 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, DistiLlama or awesome-LLM-resources?
DistiLlama: Dormant. awesome-LLM-resources: 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 DistiLlama and awesome-LLM-resources?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DistiLlama trust report; awesome-LLM-resources trust report.

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