Home/Compare/DeepSeek-R1 vs sacred

Comparison

DeepSeek-R1 vs sacred

Verdict

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.; pick sacred when tags unique to sacred: reproducibility, reproducible-science, machine-learning, python.

Markdown twin · DeepSeek-R1 alternatives · sacred alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
sacred logo

sacred

IDSIA/sacred

4.4kpushed Oct 22, 2025

Trust & integrity

SignalDeepSeek-R1sacred
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Slowing (262d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization 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 criticals
As of today · osv@v1

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
sacred
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

Stars

DeepSeek-R1
92k
sacred
4.4k

Forks

DeepSeek-R1
12k
sacred
392

Open issues

DeepSeek-R1
45
sacred
107

Language

DeepSeek-R1
-
sacred
Python

Adopt for

DeepSeek-R1
DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.
sacred
-

Persona

DeepSeek-R1
-
sacred
-

Runtime

DeepSeek-R1
-
sacred
-

License

DeepSeek-R1
MIT
sacred
MIT

Last pushed

DeepSeek-R1
Jun 27, 2025
sacred
Oct 22, 2025

Categories

DeepSeek-R1
Model Training, LLM Frameworks
sacred
Model Training, LLM Frameworks

Trust and health

Maintenance

DeepSeek-R1
Dormant (18%)
sacred
Slowing (36%)

Days since push

DeepSeek-R1
379d
sacred
262d

Open issues (now)

DeepSeek-R1
45
sacred
107

Security scan

DeepSeek-R1
No lockfile
sacred
No criticals

Full report

DeepSeek-R1
Trust report

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: derived models, mit license, distilled models, commercial use.
  • 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.

Choose sacred if…

  • Tags unique to sacred: reproducibility, reproducible-science, machine-learning, python.
  • More recently updated (last pushed Oct 22, 2025).

When NOT to use sacred

  • Last GitHub push was 262 days ago (slowing maintenance, Oct 22, 2025). Validate activity before betting a new project on sacred.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Explore

Sources

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

GitHub stars on cards: DeepSeek-R1 92k · sacred 4.4k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and sacred?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. sacred: Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over sacred?
Choose DeepSeek-R1 over sacred 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: derived models, mit license, distilled models, commercial use; 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 choose sacred over DeepSeek-R1?
Choose sacred over DeepSeek-R1 when Tags unique to sacred: reproducibility, reproducible-science, machine-learning, python; More recently updated (last pushed Oct 22, 2025).
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.
When should I avoid sacred?
Last GitHub push was 262 days ago (slowing maintenance, Oct 22, 2025). Validate activity before betting a new project on sacred. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is DeepSeek-R1 or sacred more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 4,367). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and sacred open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, sacred: MIT).
Where can I find alternatives to DeepSeek-R1 or sacred?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and sacred alternatives (DeepSeek-R1 markdown twin, sacred 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, DeepSeek-R1 or sacred?
DeepSeek-R1: Dormant. sacred: 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 DeepSeek-R1 and sacred?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; sacred trust report.