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Comparison

DeepSeek-R1 vs LlamaFactory

Verdict

Pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use; pick LlamaFactory if llamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.

Markdown twin · DeepSeek-R1 alternatives · LlamaFactory alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

★ 92kpushed Jun 27, 2025
vs
LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

★ 73kpushed Jul 10, 2026

Trust & integrity

SignalDeepSeek-R1LlamaFactory
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Very active (0d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of 1d · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No lockfile
As of 1d · none
DeepSeek-R1 trust reportLlamaFactory trust reportTrust methodology

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs

Stars

DeepSeek-R1
92k
LlamaFactory
73k

Forks

DeepSeek-R1
12k
LlamaFactory
8.9k

Open issues

DeepSeek-R1
45
LlamaFactory
1.1k

Language

DeepSeek-R1
-
LlamaFactory
Python

Adopt for

DeepSeek-R1
DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.
LlamaFactory
LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.

Persona

DeepSeek-R1
-
LlamaFactory
-

Runtime

DeepSeek-R1
-
LlamaFactory
-

License

DeepSeek-R1
MIT
LlamaFactory
Apache-2.0

Last pushed

DeepSeek-R1
Jun 27, 2025
LlamaFactory
Jul 10, 2026

Categories

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

Trust and health

Maintenance

DeepSeek-R1
Dormant (18%)
LlamaFactory
Very active (96%)

Days since push

DeepSeek-R1
379d
LlamaFactory
0d

Open issues (now)

DeepSeek-R1
45
LlamaFactory
1.1k

Owner type

DeepSeek-R1
Organization
LlamaFactory
User

Full report

DeepSeek-R1
Trust report
LlamaFactory
Trust report

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, LlamaFactory is Apache-2.0.
  • 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.
  • 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.
GitHubDetails

Choose LlamaFactory if…

  • License: LlamaFactory is Apache-2.0, DeepSeek-R1 is MIT.
  • Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning.
  • When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.

When NOT to use LlamaFactory

  • When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
  • If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
GitHubDetails

Explore

DeepSeek-R1 trust report →LlamaFactory trust report →LLM Frameworks category →Model Training category →All comparisonsStack workflowsTrending tools

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 · LlamaFactory 73k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and LlamaFactory?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over LlamaFactory?
Choose DeepSeek-R1 over LlamaFactory when License: DeepSeek-R1 is MIT, LlamaFactory is Apache-2.0; 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; 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 LlamaFactory over DeepSeek-R1?
Choose LlamaFactory over DeepSeek-R1 when License: LlamaFactory is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
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 LlamaFactory?
When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
Is DeepSeek-R1 or LlamaFactory more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 73,157). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and LlamaFactory open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, LlamaFactory: Apache-2.0).
Where can I find alternatives to DeepSeek-R1 or LlamaFactory?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and LlamaFactory alternatives (DeepSeek-R1 markdown twin, LlamaFactory 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 LlamaFactory?
DeepSeek-R1: Dormant. LlamaFactory: Very active. 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 LlamaFactory?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; LlamaFactory trust report.