Comparison
openchat vs ChatGLM-6B
Verdict
Pick openchat if a Python library for training large language models with imperfect data using transformers; 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 efficient fine-.
Markdown twin · openchat alternatives · ChatGLM-6B alternatives
GraphCanon updated Sep 20, 2026
6views this month
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Trust & integrity
| Signal | openchat | ChatGLM-6B |
|---|---|---|
| Maintenance | Dormant (703d since push) As of Aug 17, 2026 · github_public_v1 | Dormant (813d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Aug 17, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 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
- openchat
- Advancing Open-source Language Models with Imperfect Data
- ChatGLM-6B
- An Open Bilingual Dialogue Language Model
Stars
- openchat
- 5.5k
- ChatGLM-6B
- 41k
Forks
- openchat
- 432
- ChatGLM-6B
- 5.1k
Open issues
- openchat
- 137
- ChatGLM-6B
- 605
Language
- openchat
- Python
- ChatGLM-6B
- Python
Adopt for
- openchat
- A Python library for training large language models with imperfect data using transformers.
- 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
- openchat
- -
- ChatGLM-6B
- -
Runtime
- openchat
- -
- ChatGLM-6B
- -
License
- openchat
- Apache-2.0
- ChatGLM-6B
- Apache-2.0 license, allowing for both academic and free commercial use after registration.
Last pushed
- openchat
- Sep 13, 2024
- ChatGLM-6B
- Jun 27, 2024
Categories
- openchat
- LLM Frameworks, Model Training
- ChatGLM-6B
- Inference & Serving, LLM Frameworks
Trust and health
Days since push
- openchat
- 703d
- ChatGLM-6B
- 813d
Open issues (now)
- openchat
- 137
- ChatGLM-6B
- 605
Stars delta
- openchat
- +2 (30d)
- ChatGLM-6B
- -53 (30d)
Open issues delta
- openchat
- +1 (30d)
- ChatGLM-6B
- -2 (30d)
Owner type
- openchat
- User
- ChatGLM-6B
- Organization
OSV dependency advisories
- openchat
- No lockfile (source not queried)
- ChatGLM-6B
- Published findings
Full report
- openchat
- Trust report
- ChatGLM-6B
- Trust report
Choose openchat if…
- Tags unique to openchat: apache license 2.0, cuda, large-language-models, pytorch.
- Also covers Model Training.
- You need to train models on datasets with noise or missing information
When NOT to use openchat
- If your dataset is clean and well-structured, reducing model inaccuracies
- Projects that cannot depend on Apache License 2.0 or install PyTorch with CUDA support
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.
- Also covers Inference & Serving.
- 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 (imoneoi/openchat) · observed Sep 20, 2026
- GitHub forks (imoneoi/openchat) · observed Sep 20, 2026
- Last push (imoneoi/openchat) · observed Sep 13, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zai-org/ChatGLM-6B) · observed Sep 20, 2026
- GitHub forks (zai-org/ChatGLM-6B) · observed Sep 20, 2026
- Last push (zai-org/ChatGLM-6B) · observed Jun 27, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: openchat 5.5k · ChatGLM-6B 41k (synced Sep 20, 2026).
Common questions
- What is the difference between openchat and ChatGLM-6B?
- openchat: Advancing Open-source Language Models with Imperfect Data. ChatGLM-6B: An Open Bilingual Dialogue Language Model. See the comparison table for live GitHub stats and shared categories.
- When should I choose openchat over ChatGLM-6B?
- Choose openchat over ChatGLM-6B when Tags unique to openchat: apache license 2.0, cuda, large-language-models, pytorch; Also covers Model Training; You need to train models on datasets with noise or missing information.
- When should I choose ChatGLM-6B over openchat?
- Choose ChatGLM-6B over openchat 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; Also covers Inference & Serving; 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 openchat?
- If your dataset is clean and well-structured, reducing model inaccuracies Projects that cannot depend on Apache License 2.0 or install PyTorch with CUDA support
- 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 openchat or ChatGLM-6B more popular on GitHub?
- ChatGLM-6B has more GitHub stars (40,959 vs 5,487). Stars measure visibility, not whether either tool fits your constraints.
- Are openchat and ChatGLM-6B open source?
- Yes - both are open-source projects on GitHub (openchat: Apache-2.0, ChatGLM-6B: Apache-2.0).
- Where can I find alternatives to openchat or ChatGLM-6B?
- GraphCanon lists graph-backed alternatives at openchat alternatives and ChatGLM-6B alternatives (openchat 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, openchat or ChatGLM-6B?
- openchat: Dormant. 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 openchat and ChatGLM-6B?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: openchat trust report; ChatGLM-6B trust report.