Home/Compare/LLMSurvey vs graph-of-thoughts

Comparison

LLMSurvey vs graph-of-thoughts

Verdict

Pick LLMSurvey if lLMSurvey is a repository that provides a comprehensive survey paper and resources on Large Language Models, including a beginner-friendly Chinese book and detailed content on long chain-of-thought reasoning; pick graph-of-thoughts if the Graph of Thoughts tool is designed for leveraging large language models and graph structures to solve elaborate problems.

Markdown twin · LLMSurvey alternatives · graph-of-thoughts alternatives

GraphCanon updated Sep 20, 2026

8views this month

LLMSurvey logo

LLMSurvey

RUCAIBox/LLMSurvey

★ 12kpushed Mar 11, 2025
vs
graph-of-thoughts logo

graph-of-thoughts

spcl/graph-of-thoughts

★ 2.8kpushed Mar 24, 2026

Trust & integrity

SignalLLMSurveygraph-of-thoughts
Maintenance
Dormant (555d since push)
As of Sep 18, 2026 · github_public_v1
Slowing (179d since push)
As of Sep 20, 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 20, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
No lockfile (source not queried)
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

LLMSurvey
A collection of papers and resources related to Large Language Models
graph-of-thoughts
Implementation of Graph of Thoughts for large language models problem-solving

Stars

LLMSurvey
12k
graph-of-thoughts
2.8k

Forks

LLMSurvey
930
graph-of-thoughts
216

Open issues

LLMSurvey
30
graph-of-thoughts
7

Language

LLMSurvey
Python
graph-of-thoughts
Python

Adopt for

LLMSurvey
LLMSurvey is a repository that provides a comprehensive survey paper and resources on Large Language Models, including a beginner-friendly Chinese book and detailed content on long chain-of-thought reasoning.
graph-of-thoughts
The Graph of Thoughts tool is designed for leveraging large language models and graph structures to solve elaborate problems.

Persona

LLMSurvey
-
graph-of-thoughts
-

Runtime

LLMSurvey
-
graph-of-thoughts
-

License

LLMSurvey
The license information for LLMSurvey is unknown.
graph-of-thoughts
Other

Last pushed

LLMSurvey
Mar 11, 2025
graph-of-thoughts
Mar 24, 2026

Categories

LLMSurvey
LLM Frameworks, Model Training
graph-of-thoughts
LLM Frameworks, Model Training

Trust and health

Maintenance

LLMSurvey
Dormant (18%)
graph-of-thoughts
Slowing (36%)

Days since push

LLMSurvey
555d
graph-of-thoughts
179d

Open issues (now)

LLMSurvey
30
graph-of-thoughts
7

Stars delta

LLMSurvey
+11 (30d)
graph-of-thoughts
+15 (30d)

Full report

LLMSurvey
Trust report
graph-of-thoughts
Trust report

Choose LLMSurvey if…

  • Pricing: The repository is free to access, but the Chinese book is available for purchase..
  • Requirements: Min 4 GB RAM; A basic understanding of deep learning is recommended for the Chinese book..
  • Tags unique to LLMSurvey: chain-of-thought, chatgpt, in-context-learning, instruction-tuning.
  • Use LLMSurvey when you need a detailed survey paper and resources on Large Language Models, especially if you are interested in long chain-of-thought reasoning.

When NOT to use LLMSurvey

  • Avoid LLMSurvey if you are looking for a tool that provides hands-on training or implementation of LLMs, as it focuses more on theoretical resources and surveys.
  • Do not use LLMSurvey if you require real-time updates or interactive tools for LLM development, as it primarily offers static content and resources.

Choose graph-of-thoughts if…

  • Requirements: Min 8 GB RAM.
  • Tags unique to graph-of-thoughts: graph-of-thoughts, graph-structures, prompt-engineering.
  • Use when you need to solve complex problem scenarios that require the interplay between advanced language understanding and structured problem decomposition capabilities.

When NOT to use graph-of-thoughts

  • Avoid using Graph of Thoughts for simpler, straightforward queries or when real-time performance is critical because it may introduce overhead due to its complex graph processing.
  • Do not use this tool where privacy and data security are paramount concerns if the official license does not sufficiently protect your needs.

Explore

Sources

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

GitHub stars on cards: LLMSurvey 12k · graph-of-thoughts 2.8k (synced Sep 20, 2026).

Common questions

What is the difference between LLMSurvey and graph-of-thoughts?
LLMSurvey: A collection of papers and resources related to Large Language Models. graph-of-thoughts: Implementation of Graph of Thoughts for large language models problem-solving. See the comparison table for live GitHub stats and shared categories.
When should I choose LLMSurvey over graph-of-thoughts?
Choose LLMSurvey over graph-of-thoughts when Pricing: The repository is free to access, but the Chinese book is available for purchase.; Requirements: Min 4 GB RAM; A basic understanding of deep learning is recommended for the Chinese book.; Tags unique to LLMSurvey: chain-of-thought, chatgpt, in-context-learning, instruction-tuning; Use LLMSurvey when you need a detailed survey paper and resources on Large Language Models, especially if you are interested in long chain-of-thought reasoning.
When should I choose graph-of-thoughts over LLMSurvey?
Choose graph-of-thoughts over LLMSurvey when Requirements: Min 8 GB RAM; Tags unique to graph-of-thoughts: graph-of-thoughts, graph-structures, prompt-engineering; Use when you need to solve complex problem scenarios that require the interplay between advanced language understanding and structured problem decomposition capabilities.
When should I avoid LLMSurvey?
Avoid LLMSurvey if you are looking for a tool that provides hands-on training or implementation of LLMs, as it focuses more on theoretical resources and surveys. Do not use LLMSurvey if you require real-time updates or interactive tools for LLM development, as it primarily offers static content and resources.
When should I avoid graph-of-thoughts?
Avoid using Graph of Thoughts for simpler, straightforward queries or when real-time performance is critical because it may introduce overhead due to its complex graph processing. Do not use this tool where privacy and data security are paramount concerns if the official license does not sufficiently protect your needs.
Is LLMSurvey or graph-of-thoughts more popular on GitHub?
LLMSurvey has more GitHub stars (12,216 vs 2,841). Stars measure visibility, not whether either tool fits your constraints.
Are LLMSurvey and graph-of-thoughts open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to LLMSurvey or graph-of-thoughts?
GraphCanon lists graph-backed alternatives at LLMSurvey alternatives and graph-of-thoughts alternatives (LLMSurvey markdown twin, graph-of-thoughts 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, LLMSurvey or graph-of-thoughts?
LLMSurvey: Dormant. graph-of-thoughts: Slowing. 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 LLMSurvey and graph-of-thoughts?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLMSurvey trust report; graph-of-thoughts trust report.

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