Home/Compare/DeepSeek-R1 vs RLTF

Comparison

DeepSeek-R1 vs RLTF

Verdict

Pick DeepSeek-R1 when license: DeepSeek-R1 is MIT, RLTF is BSD-3-Clause; pick RLTF when license: RLTF is BSD-3-Clause, DeepSeek-R1 is MIT.

Markdown twin · DeepSeek-R1 alternatives · RLTF alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
RLTF logo

RLTF

Zyq-scut/RLTF

135pushed Oct 5, 2024

Trust & integrity

SignalDeepSeek-R1RLTF
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Dormant (644d 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 today · none
75 low (75 low)
As of today · osv@v1

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
RLTF
Accepted by Transactions on Machine Learning Research (TMLR)

Stars

DeepSeek-R1
92k
RLTF
135

Forks

DeepSeek-R1
12k
RLTF
7

Open issues

DeepSeek-R1
45
RLTF
0

Language

DeepSeek-R1
-
RLTF
Python

Adopt for

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

Persona

DeepSeek-R1
-
RLTF
-

Runtime

DeepSeek-R1
-
RLTF
-

License

DeepSeek-R1
MIT
RLTF
BSD-3-Clause

Last pushed

DeepSeek-R1
Jun 27, 2025
RLTF
Oct 5, 2024

Categories

DeepSeek-R1
Model Training, LLM Frameworks
RLTF
Model Training

Trust and health

Days since push

DeepSeek-R1
379d
RLTF
644d

Open issues (now)

DeepSeek-R1
45
RLTF
0

Owner type

DeepSeek-R1
Organization
RLTF
User

Security scan

DeepSeek-R1
No lockfile
RLTF
75 low (75 low)

Full report

DeepSeek-R1
Trust report

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, RLTF is BSD-3-Clause.
  • 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 RLTF if…

  • License: RLTF is BSD-3-Clause, DeepSeek-R1 is MIT.
  • Tags unique to RLTF: python.
  • Leaner open-issue backlog (0).

When NOT to use RLTF

  • Last GitHub push was 644 days ago (dormant maintenance, Oct 5, 2024). Validate activity before betting a new project on RLTF.
  • 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 · RLTF 135 (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and RLTF?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. RLTF: Accepted by Transactions on Machine Learning Research (TMLR). See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over RLTF?
Choose DeepSeek-R1 over RLTF when License: DeepSeek-R1 is MIT, RLTF is BSD-3-Clause; 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 RLTF over DeepSeek-R1?
Choose RLTF over DeepSeek-R1 when License: RLTF is BSD-3-Clause, DeepSeek-R1 is MIT; Tags unique to RLTF: python; Leaner open-issue backlog (0).
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 RLTF?
Last GitHub push was 644 days ago (dormant maintenance, Oct 5, 2024). Validate activity before betting a new project on RLTF. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is DeepSeek-R1 or RLTF more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 135). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and RLTF open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, RLTF: BSD-3-Clause).
Where can I find alternatives to DeepSeek-R1 or RLTF?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and RLTF alternatives (DeepSeek-R1 markdown twin, RLTF 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 RLTF?
DeepSeek-R1: Dormant. RLTF: 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 RLTF?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; RLTF trust report.