Home/Compare/MOSS vs ChatGLM-6B

Comparison

MOSS vs ChatGLM-6B

Verdict

Pick MOSS if mOSS is an open-source conversational language model from Fudan University that supports bilingual dialogue and tool invocation. It offers various models, dialogue data, deployment, and fine-tuning code; pick ChatGLM-6B if chatGLM-6B is an open-source bilingual dialogue language model with 6.2 billion parameters, optimized for Chinese and English conversations. It supports local deployment with model quantization and offers.

Markdown twin · MOSS alternatives · ChatGLM-6B alternatives

GraphCanon updated Sep 20, 2026

7views this month

MOSS logo

MOSS

OpenMOSS/MOSS

★ 12kpushed Sep 6, 2026
vs
ChatGLM-6B logo

ChatGLM-6B

zai-org/ChatGLM-6B

★ 41kpushed Jun 27, 2024

Trust & integrity

SignalMOSSChatGLM-6B
Maintenance
Active (12d since push)
As of Sep 18, 2026 · github_public_v1
Dormant (813d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
Published findings
As of Sep 18, 2026 · osv@v1
Published findings
As of Sep 18, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

MOSS
An open-source, tool-augmented conversational language model from Fudan University
ChatGLM-6B
An Open Bilingual Dialogue Language Model

Stars

MOSS
12k
ChatGLM-6B
41k

Forks

MOSS
1.1k
ChatGLM-6B
5.1k

Open issues

MOSS
243
ChatGLM-6B
605

Language

MOSS
Python
ChatGLM-6B
Python

Adopt for

MOSS
MOSS is an open-source conversational language model from Fudan University that supports bilingual dialogue and tool invocation. It offers various models, dialogue data, deployment, and fine-tuning code.
ChatGLM-6B
ChatGLM-6B is an open-source bilingual dialogue language model with 6.2 billion parameters, optimized for Chinese and English conversations. It supports local deployment with model quantization and offers efficient fine-

Persona

MOSS
-
ChatGLM-6B
-

Runtime

MOSS
-
ChatGLM-6B
-

License

MOSS
Apache-2.0
ChatGLM-6B
Apache-2.0 license, allowing for both academic and free commercial use after registration.

Last pushed

MOSS
Sep 6, 2026
ChatGLM-6B
Jun 27, 2024

Categories

MOSS
Inference & Serving, LLM Frameworks, Model Training
ChatGLM-6B
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

MOSS
Active (82%)
ChatGLM-6B
Dormant (18%)

Days since push

MOSS
12d
ChatGLM-6B
813d

Open issues (now)

MOSS
243
ChatGLM-6B
605

Stars delta

MOSS
+39 (30d)
ChatGLM-6B
-53 (30d)

Open issues delta

MOSS
0 (30d)
ChatGLM-6B
-2 (30d)

Full report

ChatGLM-6B
Trust report

Choose MOSS if…

  • Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, large-language-models.
  • Also covers Model Training.
  • Use MOSS when you need a conversational language model that supports both Chinese and English dialogue.

When NOT to use MOSS

  • Avoid MOSS if your project requires a model that is not open-source or if you prefer proprietary solutions.
  • Do not use MOSS if your application does not require support for tool invocation or if you need a model that is not bilingual.
  • If your project has strict hardware limitations and cannot meet the minimum requirements for running MOSS, such as the need for at least 12GB of GPU memory for the 4-bit quantized version, consider a

Choose ChatGLM-6B if…

  • Pricing: The model weights are completely open for academic research and allow free commercial use after registration..
  • Requirements: Min 8 GB RAM; Local deployment requires a minimum of 6GB of VRAM in INT4 quantization level for inference and 7GB for fine-tuning..
  • Tags unique to ChatGLM-6B: bilingual, commercial-use, dialogue, fine-tuning.
  • Use ChatGLM-6B when you need a model that is optimized for both Chinese and English conversations, offering a bilingual capability that is particularly strong in these languages.

When NOT to use ChatGLM-6B

  • Avoid using ChatGLM-6B if your project requires a model that supports languages other than Chinese and English, as it is specifically optimized for these two languages.
  • Do not use ChatGLM-6B if you need a model that is larger than 6.2 billion parameters, as it may not provide the depth of understanding or generation capabilities that larger models offer.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: MOSS 12k · ChatGLM-6B 41k (synced Sep 20, 2026).

Common questions

What is the difference between MOSS and ChatGLM-6B?
MOSS: An open-source, tool-augmented conversational language model from Fudan University. ChatGLM-6B: An Open Bilingual Dialogue Language Model. See the comparison table for live GitHub stats and shared categories.
When should I choose MOSS over ChatGLM-6B?
Choose MOSS over ChatGLM-6B when Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, large-language-models; Also covers Model Training; Use MOSS when you need a conversational language model that supports both Chinese and English dialogue.
When should I choose ChatGLM-6B over MOSS?
Choose ChatGLM-6B over MOSS when Pricing: The model weights are completely open for academic research and allow free commercial use after registration.; Requirements: Min 8 GB RAM; Local deployment requires a minimum of 6GB of VRAM in INT4 quantization level for inference and 7GB for fine-tuning.; Tags unique to ChatGLM-6B: bilingual, commercial-use, dialogue, fine-tuning; Use ChatGLM-6B when you need a model that is optimized for both Chinese and English conversations, offering a bilingual capability that is particularly strong in these languages.
When should I avoid MOSS?
Avoid MOSS if your project requires a model that is not open-source or if you prefer proprietary solutions. Do not use MOSS if your application does not require support for tool invocation or if you need a model that is not bilingual. If your project has strict hardware limitations and cannot meet the minimum requirements for running MOSS, such as the need for at least 12GB of GPU memory for the 4-bit quantized version, consider a
When should I avoid ChatGLM-6B?
Avoid using ChatGLM-6B if your project requires a model that supports languages other than Chinese and English, as it is specifically optimized for these two languages. Do not use ChatGLM-6B if you need a model that is larger than 6.2 billion parameters, as it may not provide the depth of understanding or generation capabilities that larger models offer.
Is MOSS or ChatGLM-6B more popular on GitHub?
ChatGLM-6B has more GitHub stars (40,959 vs 12,253). Stars measure visibility, not whether either tool fits your constraints.
Are MOSS and ChatGLM-6B open source?
Yes - both are open-source projects on GitHub (MOSS: Apache-2.0, ChatGLM-6B: Apache-2.0).
Where can I find alternatives to MOSS or ChatGLM-6B?
GraphCanon lists graph-backed alternatives at MOSS alternatives and ChatGLM-6B alternatives (MOSS markdown twin, ChatGLM-6B 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, MOSS or ChatGLM-6B?
MOSS: Active. ChatGLM-6B: 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 MOSS and ChatGLM-6B?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: MOSS trust report; ChatGLM-6B trust report.

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