Home/Compare/DeepSeek-R1 vs rellm

Comparison

DeepSeek-R1 vs rellm

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 rellm when tags unique to rellm: llm, python, huggingface-transformers, transformers.

Markdown twin · DeepSeek-R1 alternatives · rellm alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
rellm logo

rellm

r2d4/rellm

513pushed Aug 10, 2023

Trust & integrity

SignalDeepSeek-R1rellm
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Dormant (1065d 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
No lockfile
As of today · none

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
rellm
Exact structure out of any language model completion.

Stars

DeepSeek-R1
92k
rellm
513

Forks

DeepSeek-R1
12k
rellm
23

Open issues

DeepSeek-R1
45
rellm
5

Language

DeepSeek-R1
-
rellm
Python

Adopt for

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

Persona

DeepSeek-R1
-
rellm
-

Runtime

DeepSeek-R1
-
rellm
-

License

DeepSeek-R1
MIT
rellm
MIT

Last pushed

DeepSeek-R1
Jun 27, 2025
rellm
Aug 10, 2023

Categories

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

Trust and health

Days since push

DeepSeek-R1
379d
rellm
1065d

Open issues (now)

DeepSeek-R1
45
rellm
5

Owner type

DeepSeek-R1
Organization
rellm
User

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 rellm if…

  • Tags unique to rellm: llm, python, huggingface-transformers, transformers.
  • Leaner open-issue backlog (5).

When NOT to use rellm

  • Last GitHub push was 1066 days ago (dormant maintenance, Aug 10, 2023). Validate activity before betting a new project on rellm.
  • 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.

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 · rellm 513 (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and rellm?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. rellm: Exact structure out of any language model completion.. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over rellm?
Choose DeepSeek-R1 over rellm 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 rellm over DeepSeek-R1?
Choose rellm over DeepSeek-R1 when Tags unique to rellm: llm, python, huggingface-transformers, transformers; Leaner open-issue backlog (5).
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 rellm?
Last GitHub push was 1066 days ago (dormant maintenance, Aug 10, 2023). Validate activity before betting a new project on rellm. 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.
Is DeepSeek-R1 or rellm more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 513). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and rellm open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, rellm: MIT).
Where can I find alternatives to DeepSeek-R1 or rellm?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and rellm alternatives (DeepSeek-R1 markdown twin, rellm 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 rellm?
DeepSeek-R1: Dormant. rellm: 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 rellm?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; rellm trust report.