Comparison
AutoAudit vs DeepSeek-R1
Verdict
Pick AutoAudit when tags unique to AutoAudit: cyber-security, fine-tuning, gpt, html; pick DeepSeek-R1 when pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository..
Markdown twin · AutoAudit alternatives · DeepSeek-R1 alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | AutoAudit | DeepSeek-R1 |
|---|---|---|
| Maintenance | Dormant (498d since push) As of today · github_public_v1 | Dormant (379d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of 1d · none |
Tagline
- AutoAudit
- AutoAudit—— the LLM for Cyber Security 网络安全大语言模型
- DeepSeek-R1
- Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
Stars
- AutoAudit
- 355
- DeepSeek-R1
- 92k
Forks
- AutoAudit
- 38
- DeepSeek-R1
- 12k
Open issues
- AutoAudit
- 4
- DeepSeek-R1
- 45
Language
- AutoAudit
- HTML
- DeepSeek-R1
- -
Adopt for
- AutoAudit
- -
- DeepSeek-R1
- DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.
Persona
- AutoAudit
- -
- DeepSeek-R1
- -
Runtime
- AutoAudit
- -
- DeepSeek-R1
- -
License
- AutoAudit
- MIT
- DeepSeek-R1
- MIT
Last pushed
- AutoAudit
- Feb 28, 2025
- DeepSeek-R1
- Jun 27, 2025
Categories
- AutoAudit
- LLM Frameworks, Model Training
- DeepSeek-R1
- LLM Frameworks, Model Training
Trust and health
Days since push
- AutoAudit
- 498d
- DeepSeek-R1
- 379d
Open issues (now)
- AutoAudit
- 4
- DeepSeek-R1
- 45
Owner type
- AutoAudit
- User
- DeepSeek-R1
- Organization
Full report
- AutoAudit
- Trust report
- DeepSeek-R1
- Trust report
Choose AutoAudit if…
- Tags unique to AutoAudit: cyber-security, fine-tuning, gpt, html.
- Leaner open-issue backlog (4).
When NOT to use AutoAudit
- Last GitHub push was 499 days ago (dormant maintenance, Feb 28, 2025). Validate activity before betting a new project on AutoAudit.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose DeepSeek-R1 if…
- Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository..
- Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs..
- Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license.
- When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.
When NOT to use DeepSeek-R1
- Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments.
- If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ddzipp/AutoAudit) · observed Jul 11, 2026
- GitHub forks (ddzipp/AutoAudit) · observed Jul 11, 2026
- Last push (ddzipp/AutoAudit) · observed Feb 28, 2025
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (deepseek-ai/DeepSeek-R1) · observed Jul 12, 2026
- GitHub forks (deepseek-ai/DeepSeek-R1) · observed Jul 12, 2026
- Last push (deepseek-ai/DeepSeek-R1) · observed Jun 27, 2025
- License file (MIT) · observed Jul 12, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: AutoAudit 355 · DeepSeek-R1 92k (synced Jul 11, 2026).
Common questions
- What is the difference between AutoAudit and DeepSeek-R1?
- AutoAudit: AutoAudit—— the LLM for Cyber Security 网络安全大语言模型. DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. See the comparison table for live GitHub stats and shared categories.
- When should I choose AutoAudit over DeepSeek-R1?
- Choose AutoAudit over DeepSeek-R1 when Tags unique to AutoAudit: cyber-security, fine-tuning, gpt, html; Leaner open-issue backlog (4).
- When should I choose DeepSeek-R1 over AutoAudit?
- Choose DeepSeek-R1 over AutoAudit when Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.; Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.; Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license; When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.
- When should I avoid AutoAudit?
- Last GitHub push was 499 days ago (dormant maintenance, Feb 28, 2025). Validate activity before betting a new project on AutoAudit. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- When should I avoid DeepSeek-R1?
- Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.
- Is AutoAudit or DeepSeek-R1 more popular on GitHub?
- DeepSeek-R1 has more GitHub stars (91,991 vs 355). Stars measure visibility, not whether either tool fits your constraints.
- Are AutoAudit and DeepSeek-R1 open source?
- Yes - both are open-source projects on GitHub (AutoAudit: MIT, DeepSeek-R1: MIT).
- Where can I find alternatives to AutoAudit or DeepSeek-R1?
- GraphCanon lists graph-backed alternatives at AutoAudit alternatives and DeepSeek-R1 alternatives (AutoAudit markdown twin, DeepSeek-R1 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, AutoAudit or DeepSeek-R1?
- AutoAudit: Dormant. DeepSeek-R1: 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 AutoAudit and DeepSeek-R1?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AutoAudit trust report; DeepSeek-R1 trust report.