Home/Compare/DeepSeek-R1 vs pai

Comparison

DeepSeek-R1 vs pai

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 pai when tags unique to pai: gpu, cluster-manager, ai, artificial-intelligence.

Markdown twin · DeepSeek-R1 alternatives · pai alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
pai logo

pai

microsoft/pai

2.7kpushed Jun 6, 2024

Trust & integrity

SignalDeepSeek-R1pai
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Archived (765d 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
No lockfile
As of today · none

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
pai
Resource scheduling and cluster management for AI

Stars

DeepSeek-R1
92k
pai
2.7k

Forks

DeepSeek-R1
12k
pai
549

Open issues

DeepSeek-R1
45
pai
282

Language

DeepSeek-R1
-
pai
JavaScript

Adopt for

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

Persona

DeepSeek-R1
-
pai
-

Runtime

DeepSeek-R1
-
pai
-

License

DeepSeek-R1
MIT
pai
MIT

Last pushed

DeepSeek-R1
Jun 27, 2025
pai
Jun 6, 2024

Categories

DeepSeek-R1
LLM Frameworks, Model Training
pai
Model Training

Trust and health

Maintenance

DeepSeek-R1
Dormant (18%)
pai
Archived (8%)

Days since push

DeepSeek-R1
379d
pai
765d

Archived on GitHub

DeepSeek-R1
No
pai
Yes

Open issues (now)

DeepSeek-R1
45
pai
282

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.
  • 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 pai if…

  • Tags unique to pai: gpu, cluster-manager, ai, artificial-intelligence.

When NOT to use pai

  • pai is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
  • 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 · pai 2.7k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and pai?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. pai: Resource scheduling and cluster management for AI. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over pai?
Choose DeepSeek-R1 over pai 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; 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 pai over DeepSeek-R1?
Choose pai over DeepSeek-R1 when Tags unique to pai: gpu, cluster-manager, ai, artificial-intelligence.
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 pai?
pai is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is DeepSeek-R1 or pai more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 2,683). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and pai open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, pai: MIT).
Where can I find alternatives to DeepSeek-R1 or pai?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and pai alternatives (DeepSeek-R1 markdown twin, pai 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 pai?
DeepSeek-R1: Dormant. pai: Archived. 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 pai?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; pai trust report.