Home/Compare/DeepSeek-R1 vs lux

Comparison

DeepSeek-R1 vs lux

Verdict

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

Markdown twin · DeepSeek-R1 alternatives · lux alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
lux logo

lux

lux-org/lux

5.4kpushed Mar 20, 2024

Trust & integrity

SignalDeepSeek-R1lux
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Dormant (843d 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
13 low (13 low)
As of today · osv@v1

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
lux
Automatically visualize your pandas dataframe via a single print! 📊 💡

Stars

DeepSeek-R1
92k
lux
5.4k

Forks

DeepSeek-R1
12k
lux
380

Open issues

DeepSeek-R1
45
lux
90

Language

DeepSeek-R1
-
lux
Python

Adopt for

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

Persona

DeepSeek-R1
-
lux
-

Runtime

DeepSeek-R1
-
lux
-

License

DeepSeek-R1
MIT
lux
Apache-2.0

Last pushed

DeepSeek-R1
Jun 27, 2025
lux
Mar 20, 2024

Categories

DeepSeek-R1
Model Training, LLM Frameworks
lux
Model Training

Trust and health

Days since push

DeepSeek-R1
379d
lux
843d

Open issues (now)

DeepSeek-R1
45
lux
90

Security scan

DeepSeek-R1
No lockfile
lux
13 low (13 low)

Full report

DeepSeek-R1
Trust report

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, lux 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.
  • Also covers LLM Frameworks.
  • 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 lux if…

  • License: lux is Apache-2.0, DeepSeek-R1 is MIT.
  • Tags unique to lux: data-science, exploratory-data-analysis, python, jupyter.

When NOT to use lux

  • Last GitHub push was 843 days ago (dormant maintenance, Mar 20, 2024). Validate activity before betting a new project on lux.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

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 · lux 5.4k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and lux?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. lux: Automatically visualize your pandas dataframe via a single print! 📊 💡. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over lux?
Choose DeepSeek-R1 over lux when License: DeepSeek-R1 is MIT, lux 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; Also covers LLM Frameworks; 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 lux over DeepSeek-R1?
Choose lux over DeepSeek-R1 when License: lux is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to lux: data-science, exploratory-data-analysis, python, jupyter.
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 lux?
Last GitHub push was 843 days ago (dormant maintenance, Mar 20, 2024). Validate activity before betting a new project on lux. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is DeepSeek-R1 or lux more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 5,380). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and lux open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, lux: Apache-2.0).
Where can I find alternatives to DeepSeek-R1 or lux?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and lux alternatives (DeepSeek-R1 markdown twin, lux 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 lux?
DeepSeek-R1: Dormant. lux: 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 DeepSeek-R1 and lux?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; lux trust report.