Home/Compare/jailbreak-evaluation vs DeepSeek-R1

Comparison

jailbreak-evaluation vs DeepSeek-R1

Verdict

Pick jailbreak-evaluation when license: jailbreak-evaluation is Apache-2.0, DeepSeek-R1 is MIT; pick DeepSeek-R1 when license: DeepSeek-R1 is MIT, jailbreak-evaluation is Apache-2.0.

Markdown twin · jailbreak-evaluation alternatives · DeepSeek-R1 alternatives

GraphCanon updated today

jailbreak-evaluation logo

jailbreak-evaluation

controllability/jailbreak-evaluation

27pushed Nov 4, 2024
vs
DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025

Trust & integrity

Signaljailbreak-evaluationDeepSeek-R1
Maintenance
Dormant (614d since push)
As of today · github_public_v1
Dormant (379d 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 lockfile
As of today · none

Tagline

jailbreak-evaluation
The jailbreak-evaluation is an easy-to-use Python package for language model jailbreak evaluation.
DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.

Stars

jailbreak-evaluation
27
DeepSeek-R1
92k

Forks

jailbreak-evaluation
8
DeepSeek-R1
12k

Open issues

jailbreak-evaluation
0
DeepSeek-R1
45

Language

jailbreak-evaluation
Python
DeepSeek-R1
-

Adopt for

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

Persona

jailbreak-evaluation
-
DeepSeek-R1
-

Runtime

jailbreak-evaluation
-
DeepSeek-R1
-

License

jailbreak-evaluation
Apache-2.0
DeepSeek-R1
MIT

Last pushed

jailbreak-evaluation
Nov 4, 2024
DeepSeek-R1
Jun 27, 2025

Categories

jailbreak-evaluation
LLM Frameworks, Model Training, Evaluation & Observability
DeepSeek-R1
Model Training, LLM Frameworks

Trust and health

Days since push

jailbreak-evaluation
614d
DeepSeek-R1
379d

Open issues (now)

jailbreak-evaluation
0
DeepSeek-R1
45

Full report

jailbreak-evaluation
Trust report
DeepSeek-R1
Trust report

Choose jailbreak-evaluation if…

  • License: jailbreak-evaluation is Apache-2.0, DeepSeek-R1 is MIT.
  • Tags unique to jailbreak-evaluation: python.
  • Also covers Evaluation & Observability.

When NOT to use jailbreak-evaluation

  • Last GitHub push was 614 days ago (dormant maintenance, Nov 4, 2024). Validate activity before betting a new project on jailbreak-evaluation.
  • 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.
  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, jailbreak-evaluation is Apache-2.0.
  • 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.

Explore

Sources

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

GitHub stars on cards: jailbreak-evaluation 27 · DeepSeek-R1 92k (synced Jul 11, 2026).

Common questions

What is the difference between jailbreak-evaluation and DeepSeek-R1?
jailbreak-evaluation: The jailbreak-evaluation is an easy-to-use Python package for language model jailbreak evaluation.. 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 jailbreak-evaluation over DeepSeek-R1?
Choose jailbreak-evaluation over DeepSeek-R1 when License: jailbreak-evaluation is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to jailbreak-evaluation: python; Also covers Evaluation & Observability.
When should I choose DeepSeek-R1 over jailbreak-evaluation?
Choose DeepSeek-R1 over jailbreak-evaluation when License: DeepSeek-R1 is MIT, jailbreak-evaluation is Apache-2.0; 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 avoid jailbreak-evaluation?
Last GitHub push was 614 days ago (dormant maintenance, Nov 4, 2024). Validate activity before betting a new project on jailbreak-evaluation. 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. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
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 jailbreak-evaluation or DeepSeek-R1 more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 27). Stars measure visibility, not whether either tool fits your constraints.
Are jailbreak-evaluation and DeepSeek-R1 open source?
Yes - both are open-source projects on GitHub (jailbreak-evaluation: Apache-2.0, DeepSeek-R1: MIT).
Where can I find alternatives to jailbreak-evaluation or DeepSeek-R1?
GraphCanon lists graph-backed alternatives at jailbreak-evaluation alternatives and DeepSeek-R1 alternatives (jailbreak-evaluation 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, jailbreak-evaluation or DeepSeek-R1?
jailbreak-evaluation: 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 jailbreak-evaluation and DeepSeek-R1?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: jailbreak-evaluation trust report; DeepSeek-R1 trust report.