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Home/Compare/DeepSeek-R1 vs GLM-130B

Comparison

DeepSeek-R1 vs GLM-130B

Verdict

Pick DeepSeek-R1 when license: DeepSeek-R1 is MIT, GLM-130B is Apache-2.0; pick GLM-130B when license: GLM-130B is Apache-2.0, DeepSeek-R1 is MIT.

Markdown twin · DeepSeek-R1 alternatives · GLM-130B alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

★ 92kpushed Jun 27, 2025
vs
GLM-130B logo

GLM-130B

zai-org/GLM-130B

★ 7.7kpushed Jul 25, 2023

Trust & integrity

SignalDeepSeek-R1GLM-130B
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Dormant (1082d 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 1d · none
No criticals
As of today · osv@v1
DeepSeek-R1 trust reportGLM-130B trust reportTrust methodology

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
GLM-130B
GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)

Stars

DeepSeek-R1
92k
GLM-130B
7.7k

Forks

DeepSeek-R1
12k
GLM-130B
601

Open issues

DeepSeek-R1
45
GLM-130B
124

Language

DeepSeek-R1
-
GLM-130B
Python

Adopt for

DeepSeek-R1
DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.
GLM-130B
-

Persona

DeepSeek-R1
-
GLM-130B
-

Runtime

DeepSeek-R1
-
GLM-130B
-

License

DeepSeek-R1
MIT
GLM-130B
Apache-2.0

Last pushed

DeepSeek-R1
Jun 27, 2025
GLM-130B
Jul 25, 2023

Categories

DeepSeek-R1
LLM Frameworks, Model Training
GLM-130B
Model Training

Trust and health

Days since push

DeepSeek-R1
379d
GLM-130B
1082d

Open issues (now)

DeepSeek-R1
45
GLM-130B
124

Security scan

DeepSeek-R1
No lockfile
GLM-130B
No criticals

Full report

DeepSeek-R1
Trust report
GLM-130B
Trust report

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, GLM-130B 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.
  • 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.
GitHubDetails

Choose GLM-130B if…

  • License: GLM-130B is Apache-2.0, DeepSeek-R1 is MIT.
  • Tags unique to GLM-130B: python.

When NOT to use GLM-130B

  • Last GitHub push was 1083 days ago (dormant maintenance, Jul 25, 2023). Validate activity before betting a new project on GLM-130B.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
GitHubDetails

Explore

DeepSeek-R1 trust report →GLM-130B 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 · GLM-130B 7.7k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and GLM-130B?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. GLM-130B: GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023). See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over GLM-130B?
Choose DeepSeek-R1 over GLM-130B when License: DeepSeek-R1 is MIT, GLM-130B 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; 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 GLM-130B over DeepSeek-R1?
Choose GLM-130B over DeepSeek-R1 when License: GLM-130B is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to GLM-130B: python.
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 GLM-130B?
Last GitHub push was 1083 days ago (dormant maintenance, Jul 25, 2023). Validate activity before betting a new project on GLM-130B. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is DeepSeek-R1 or GLM-130B more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 7,656). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and GLM-130B open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, GLM-130B: Apache-2.0).
Where can I find alternatives to DeepSeek-R1 or GLM-130B?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and GLM-130B alternatives (DeepSeek-R1 markdown twin, GLM-130B 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 GLM-130B?
DeepSeek-R1: Dormant. GLM-130B: 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 GLM-130B?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; GLM-130B trust report.