Home/Compare/DeepSeek-R1 vs pallms

Comparison

DeepSeek-R1 vs pallms

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 pallms when more recently updated (last pushed Jan 13, 2026).

Markdown twin · DeepSeek-R1 alternatives · pallms alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
pallms logo

pallms

mik0w/pallms

141pushed Jan 13, 2026

Trust & integrity

SignalDeepSeek-R1pallms
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Slowing (179d 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.
pallms
Payloads for Attacking Large Language Models

Stars

DeepSeek-R1
92k
pallms
141

Forks

DeepSeek-R1
12k
pallms
17

Open issues

DeepSeek-R1
45
pallms
0

Language

DeepSeek-R1
-
pallms
-

Adopt for

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

Persona

DeepSeek-R1
-
pallms
-

Runtime

DeepSeek-R1
-
pallms
-

License

DeepSeek-R1
MIT
pallms
MIT

Last pushed

DeepSeek-R1
Jun 27, 2025
pallms
Jan 13, 2026

Categories

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

Trust and health

Maintenance

DeepSeek-R1
Dormant (18%)
pallms
Slowing (36%)

Days since push

DeepSeek-R1
379d
pallms
179d

Open issues (now)

DeepSeek-R1
45
pallms
0

Owner type

DeepSeek-R1
Organization
pallms
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 pallms if…

  • More recently updated (last pushed Jan 13, 2026).

When NOT to use pallms

  • Last GitHub push was 179 days ago (slowing maintenance, Jan 13, 2026). Validate activity before betting a new project on pallms.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

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 · pallms 141 (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and pallms?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. pallms: Payloads for Attacking Large Language Models. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over pallms?
Choose DeepSeek-R1 over pallms 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 pallms over DeepSeek-R1?
Choose pallms over DeepSeek-R1 when More recently updated (last pushed Jan 13, 2026).
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 pallms?
Last GitHub push was 179 days ago (slowing maintenance, Jan 13, 2026). Validate activity before betting a new project on pallms. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is DeepSeek-R1 or pallms more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 141). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and pallms open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, pallms: MIT).
Where can I find alternatives to DeepSeek-R1 or pallms?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and pallms alternatives (DeepSeek-R1 markdown twin, pallms 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 pallms?
DeepSeek-R1: Dormant. pallms: Slowing. 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 pallms?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; pallms trust report.