Comparison
octopack vs CodeGeeX
Verdict
Pick octopack if octoPack is an instruction tuning code large language models repository providing detailed components for model training with data retrieval; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration.
Markdown twin · octopack alternatives · CodeGeeX alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | octopack | CodeGeeX |
|---|---|---|
| Maintenance | Dormant (545d since push) As of 2w · github_public_v1 | Dormant (719d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · 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
- octopack
- OctoPack: Instruction Tuning Code Large Language Models
- CodeGeeX
- CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.
Stars
- octopack
- 479
- CodeGeeX
- 8.8k
Forks
- octopack
- 29
- CodeGeeX
- 688
Open issues
- octopack
- 14
- CodeGeeX
- 188
Language
- octopack
- Jupyter Notebook
- CodeGeeX
- Python
Adopt for
- octopack
- OctoPack is an instruction tuning code large language models repository providing detailed components for model training with data retrieval.
- CodeGeeX
- CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration.
Persona
- octopack
- -
- CodeGeeX
- -
Runtime
- octopack
- -
- CodeGeeX
- -
License
- octopack
- MIT
- CodeGeeX
- Apache-2.0
Last pushed
- octopack
- Feb 5, 2025
- CodeGeeX
- Aug 13, 2024
Categories
- octopack
- Data & Retrieval, Model Training
- CodeGeeX
- LLM Frameworks, Model Training
Trust and health
Days since push
- octopack
- 545d
- CodeGeeX
- 719d
Open issues (now)
- octopack
- 14
- CodeGeeX
- 188
OSV dependency advisories
- octopack
- No lockfile (source not queried)
- CodeGeeX
- Published findings
Full report
- octopack
- Trust report
- CodeGeeX
- Trust report
Choose octopack if…
- octopack is primarily Jupyter Notebook; CodeGeeX is Python.
- License: octopack is MIT, CodeGeeX is Apache-2.0.
- Tags unique to octopack: code-llm, dataset, evaluation, instruction-tuning.
- Also covers Data & Retrieval.
- When you need to fine-tune StarCoder or CodeGeeX2 on commit message datasets formatted as instructions
When NOT to use octopack
- If your project does not require instruction tuning and focuses solely on general model improvements
- When your data source is limited to English or a few languages, excluding the need for broad linguistic coverage as provided by CommitPack
Choose CodeGeeX if…
- CodeGeeX is primarily Python; octopack is Jupyter Notebook.
- License: CodeGeeX is Apache-2.0, octopack is MIT.
- Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models.
- Also covers LLM Frameworks.
- When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability.
When NOT to use CodeGeeX
- If your development environment lacks the necessary dependencies like Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.
- In scenarios where an open-source solution is not preferable or when support for exclusively one language's syntax is sufficient.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bigcode-project/octopack) · observed Aug 5, 2026
- GitHub forks (bigcode-project/octopack) · observed Aug 5, 2026
- Last push (bigcode-project/octopack) · observed Feb 5, 2025
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zai-org/CodeGeeX) · observed Aug 2, 2026
- GitHub forks (zai-org/CodeGeeX) · observed Aug 2, 2026
- Last push (zai-org/CodeGeeX) · observed Aug 13, 2024
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: octopack 479 · CodeGeeX 8.8k (synced Aug 5, 2026).
Common questions
- What is the difference between octopack and CodeGeeX?
- octopack: OctoPack: Instruction Tuning Code Large Language Models. CodeGeeX: CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.. See the comparison table for live GitHub stats and shared categories.
- When should I choose octopack over CodeGeeX?
- Choose octopack over CodeGeeX when octopack is primarily Jupyter Notebook; CodeGeeX is Python; License: octopack is MIT, CodeGeeX is Apache-2.0; Tags unique to octopack: code-llm, dataset, evaluation, instruction-tuning; Also covers Data & Retrieval; When you need to fine-tune StarCoder or CodeGeeX2 on commit message datasets formatted as instructions.
- When should I choose CodeGeeX over octopack?
- Choose CodeGeeX over octopack when CodeGeeX is primarily Python; octopack is Jupyter Notebook; License: CodeGeeX is Apache-2.0, octopack is MIT; Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models; Also covers LLM Frameworks; When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability.
- When should I avoid octopack?
- If your project does not require instruction tuning and focuses solely on general model improvements When your data source is limited to English or a few languages, excluding the need for broad linguistic coverage as provided by CommitPack
- When should I avoid CodeGeeX?
- If your development environment lacks the necessary dependencies like Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+. In scenarios where an open-source solution is not preferable or when support for exclusively one language's syntax is sufficient.
- Is octopack or CodeGeeX more popular on GitHub?
- CodeGeeX has more GitHub stars (8,809 vs 479). Stars measure visibility, not whether either tool fits your constraints.
- Are octopack and CodeGeeX open source?
- Yes - both are open-source projects on GitHub (octopack: MIT, CodeGeeX: Apache-2.0).
- Where can I find alternatives to octopack or CodeGeeX?
- GraphCanon lists graph-backed alternatives at octopack alternatives and CodeGeeX alternatives (octopack markdown twin, CodeGeeX 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, octopack or CodeGeeX?
- octopack: Dormant. CodeGeeX: 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 octopack and CodeGeeX?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: octopack trust report; CodeGeeX trust report.