Home/Compare/DeepSeek-R1 vs automl-gs

Comparison

DeepSeek-R1 vs automl-gs

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 automl-gs when tags unique to automl-gs: automl, keras, machine-learning, python.

Markdown twin · DeepSeek-R1 alternatives · automl-gs alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
automl-gs logo

automl-gs

minimaxir/automl-gs

1.9kpushed Oct 22, 2019

Trust & integrity

SignalDeepSeek-R1automl-gs
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Dormant (2454d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
2 high, 5 medium, 7 low (2 high, 5 medium, 7 low)
As of today · osv@v1

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
automl-gs
Provide an input CSV and a target field to predict, generate a model + code to run it.

Stars

DeepSeek-R1
92k
automl-gs
1.9k

Forks

DeepSeek-R1
12k
automl-gs
181

Open issues

DeepSeek-R1
45
automl-gs
28

Language

DeepSeek-R1
-
automl-gs
Python

Adopt for

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

Persona

DeepSeek-R1
-
automl-gs
-

Runtime

DeepSeek-R1
-
automl-gs
-

License

DeepSeek-R1
MIT
automl-gs
MIT

Last pushed

DeepSeek-R1
Jun 27, 2025
automl-gs
Oct 22, 2019

Categories

DeepSeek-R1
LLM Frameworks, Model Training
automl-gs
Model Training

Trust and health

Days since push

DeepSeek-R1
379d
automl-gs
2454d

Open issues (now)

DeepSeek-R1
45
automl-gs
28

Owner type

DeepSeek-R1
Organization
automl-gs
User

Security scan

DeepSeek-R1
No lockfile
automl-gs
2 high, 5 medium, 7 low (2 high, 5 medium, 7 low)

Full report

DeepSeek-R1
Trust report
automl-gs
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: commercial use, derived models, distilled models, mit license.
  • 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 automl-gs if…

  • Tags unique to automl-gs: automl, keras, machine-learning, python.
  • Leaner open-issue backlog (28).

When NOT to use automl-gs

  • Last GitHub push was 2454 days ago (dormant maintenance, Oct 22, 2019). Validate activity before betting a new project on automl-gs.
  • 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 · automl-gs 1.9k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and automl-gs?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. automl-gs: Provide an input CSV and a target field to predict, generate a model + code to run it.. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over automl-gs?
Choose DeepSeek-R1 over automl-gs 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; 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 automl-gs over DeepSeek-R1?
Choose automl-gs over DeepSeek-R1 when Tags unique to automl-gs: automl, keras, machine-learning, python; Leaner open-issue backlog (28).
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 automl-gs?
Last GitHub push was 2454 days ago (dormant maintenance, Oct 22, 2019). Validate activity before betting a new project on automl-gs. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is DeepSeek-R1 or automl-gs more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 1,866). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and automl-gs open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, automl-gs: MIT).
Where can I find alternatives to DeepSeek-R1 or automl-gs?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and automl-gs alternatives (DeepSeek-R1 markdown twin, automl-gs 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 automl-gs?
DeepSeek-R1: Dormant. automl-gs: 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 automl-gs?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; automl-gs trust report.