Comparison
cceval vs CodeGeeX
Verdict
Pick cceval if cceval is designed for assessing cross-file code completion capabilities in multilingual environments across different setups and retrieval methods; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model that supports both Mindspore and PyTorch frameworks, making it suitable for developers working with Ascend 910 AI Processors or GPU platforms.
Markdown twin · cceval alternatives · CodeGeeX alternatives
GraphCanon updated Oct 8, 2026
vs
Trust & integrity
| Signal | cceval | CodeGeeX |
|---|---|---|
| Maintenance | Dormant (418d since push) As of Oct 8, 2026 · github_public_v1 | Dormant (766d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 8, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings 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
- cceval
- CrossCodeEval Benchmark for Cross-File Code Completion
- CodeGeeX
- CodeGeeX: An Open Multilingual Code Generation Model
Stars
- cceval
- 184
- CodeGeeX
- 8.8k
Forks
- cceval
- 29
- CodeGeeX
- 686
Open issues
- cceval
- 5
- CodeGeeX
- 189
Language
- cceval
- Python
- CodeGeeX
- Python
Adopt for
- cceval
- cceval is designed for assessing cross-file code completion capabilities in multilingual environments across different setups and retrieval methods.
- CodeGeeX
- CodeGeeX is an open-source multilingual code generation model that supports both Mindspore and PyTorch frameworks, making it suitable for developers working with Ascend 910 AI Processors or GPU platforms.
Persona
- cceval
- -
- CodeGeeX
- -
Runtime
- cceval
- -
- CodeGeeX
- -
License
- cceval
- Apache-2.0
- CodeGeeX
- CodeGeeX is licensed under the Apache-2.0 license, allowing for broad use, modification, and distribution of the code, while the model itself is under a separate license.
Last pushed
- cceval
- Aug 15, 2025
- CodeGeeX
- Aug 13, 2024
Categories
- cceval
- Evaluation & Observability
- CodeGeeX
- LLM Frameworks, Model Training
Trust and health
Days since push
- cceval
- 418d
- CodeGeeX
- 766d
Open issues (now)
- cceval
- 5
- CodeGeeX
- 189
Stars delta
- cceval
- +2 (30d)
- CodeGeeX
- -3 (30d)
Open issues delta
- cceval
- 0 (30d)
- CodeGeeX
- +1 (30d)
Full report
- cceval
- Trust report
- CodeGeeX
- Trust report
Shared compatibility
- Python · cceval: Python runtime · CodeGeeX: Python runtime
Choose cceval if…
- Tags unique to cceval: benchmark, code-completion, cross-file, evaluation-tool.
- Also covers Evaluation & Observability.
- You need to evaluate the performance of cross-file code completion systems that can handle multiple programming languages simultaneously
When NOT to use cceval
- Your evaluation needs are focused solely on single-file or intralingual code completion benchmarks
- You require real-time data access or live updates; cceval provides pre-packaged datasets that need to be manually obtained and uncompressed
Choose CodeGeeX if…
- Requirements: Requires Docker; Requires Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.; Supports installation via pip or through a Docker container for quick setup..
- Tags unique to CodeGeeX: code-generation, code-generation-model, gpu-support, mindspore.
- Also covers LLM Frameworks, Model Training.
- When you need a multilingual code generation model that supports both Mindspore and PyTorch frameworks, allowing flexibility between Ascend 910 AI Processors and GPU platforms.
When NOT to use CodeGeeX
- If your project is strictly limited to TensorFlow or other frameworks not supported by CodeGeeX, as it primarily supports Mindspore and PyTorch.
- When your development environment does not support Python 3.7+, CUDA 11+, PyTorch 1.10+, or DeepSpeed 0.6+, as these are the minimum requirements for running CodeGeeX.
- If you are looking for a model that does not require specific hardware like Ascend 910 AI Processors or GPUs, as CodeGeeX is optimized for these platforms.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (amazon-science/cceval) · observed Oct 8, 2026
- GitHub forks (amazon-science/cceval) · observed Oct 8, 2026
- Last push (amazon-science/cceval) · observed Aug 15, 2025
- License file (Apache-2.0) · observed Oct 8, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zai-org/CodeGeeX) · observed Sep 20, 2026
- GitHub forks (zai-org/CodeGeeX) · observed Sep 20, 2026
- Last push (zai-org/CodeGeeX) · observed Aug 13, 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: cceval 184 · CodeGeeX 8.8k (synced Oct 8, 2026).
Common questions
- What is the difference between cceval and CodeGeeX?
- cceval: CrossCodeEval Benchmark for Cross-File Code Completion. CodeGeeX: CodeGeeX: An Open Multilingual Code Generation Model. See the comparison table for live GitHub stats and shared categories.
- When should I choose cceval over CodeGeeX?
- Choose cceval over CodeGeeX when Tags unique to cceval: benchmark, code-completion, cross-file, evaluation-tool; Also covers Evaluation & Observability; You need to evaluate the performance of cross-file code completion systems that can handle multiple programming languages simultaneously.
- When should I choose CodeGeeX over cceval?
- Choose CodeGeeX over cceval when Requirements: Requires Docker; Requires Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.; Supports installation via pip or through a Docker container for quick setup.; Tags unique to CodeGeeX: code-generation, code-generation-model, gpu-support, mindspore; Also covers LLM Frameworks, Model Training; When you need a multilingual code generation model that supports both Mindspore and PyTorch frameworks, allowing flexibility between Ascend 910 AI Processors and GPU platforms.
- When should I avoid cceval?
- Your evaluation needs are focused solely on single-file or intralingual code completion benchmarks You require real-time data access or live updates; cceval provides pre-packaged datasets that need to be manually obtained and uncompressed
- When should I avoid CodeGeeX?
- If your project is strictly limited to TensorFlow or other frameworks not supported by CodeGeeX, as it primarily supports Mindspore and PyTorch. When your development environment does not support Python 3.7+, CUDA 11+, PyTorch 1.10+, or DeepSpeed 0.6+, as these are the minimum requirements for running CodeGeeX. If you are looking for a model that does not require specific hardware like Ascend 910 AI Processors or GPUs, as CodeGeeX is optimized for these platforms.
- Is cceval or CodeGeeX more popular on GitHub?
- CodeGeeX has more GitHub stars (8,806 vs 184). Stars measure visibility, not whether either tool fits your constraints.
- Are cceval and CodeGeeX open source?
- Yes - both are open-source projects on GitHub (cceval: Apache-2.0, CodeGeeX: Apache-2.0).
- Where can I find alternatives to cceval or CodeGeeX?
- GraphCanon lists graph-backed alternatives at cceval alternatives and CodeGeeX alternatives (cceval 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, cceval or CodeGeeX?
- cceval: 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 cceval and CodeGeeX?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: cceval trust report; CodeGeeX trust report.