Comparison
contextcheck vs deepeval
Verdict
Pick contextcheck if contextcheck, an MIT-licensed Python framework for evaluating large language models and RAG systems through configurable YAML settings that integrate with CI pipelines; pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
Markdown twin · contextcheck alternatives · deepeval alternatives
GraphCanon updated Sep 8, 2026
12views this month
vs
Trust & integrity
| Signal | contextcheck | deepeval |
|---|---|---|
| Maintenance | Dormant (635d since push) As of Sep 8, 2026 · github_public_v1 | Very active (1d since push) As of Aug 28, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 8, 2026 · github_public_v1 | Not a fork · Organization account As of Aug 28, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- contextcheck
- Framework for LLMs and RAGs testing in Python
- deepeval
- LLM Evaluation Framework.
Stars
- contextcheck
- 97
- deepeval
- 18k
Forks
- contextcheck
- 11
- deepeval
- 1.9k
Open issues
- contextcheck
- 1
- deepeval
- 485
Language
- contextcheck
- Python
- deepeval
- Python
Adopt for
- contextcheck
- Contextcheck, an MIT-licensed Python framework for evaluating large language models and RAG systems through configurable YAML settings that integrate with CI pipelines.
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
Persona
- contextcheck
- -
- deepeval
- -
Runtime
- contextcheck
- -
- deepeval
- -
License
- contextcheck
- MIT
- deepeval
- Apache-2.0 License
Last pushed
- contextcheck
- Dec 11, 2024
- deepeval
- Aug 26, 2026
Categories
- contextcheck
- Evaluation & Observability, Model Training
- deepeval
- Evaluation & Observability
Trust and health
Maintenance
- contextcheck
- Dormant (18%)
- deepeval
- Very active (96%)
Days since push
- contextcheck
- 635d
- deepeval
- 1d
Open issues (now)
- contextcheck
- 1
- deepeval
- 485
Stars delta
- contextcheck
- +1 (30d)
- deepeval
- +688 (30d)
Open issues delta
- contextcheck
- 0 (30d)
- deepeval
- +81 (30d)
Full report
- contextcheck
- Trust report
- deepeval
- Trust report
Choose contextcheck if…
- License: contextcheck is MIT, deepeval is Apache-2.0.
- Tags unique to contextcheck: ai-chat, ai-testing, chatbot-framework, ci-integration.
- Also covers Model Training.
- When you require a framework specifically designed to test the robustness of both LLMs and Retrieval-Augmented Generation systems within Python projects.
When NOT to use contextcheck
- Avoid if you aim for a framework without configuration flexibility through YAML as contextcheck strictly relies on this format for setting up test environments.
- Skip contextcheck if your project environment or requirements do not align with the MIT license terms, especially in contexts where licensing compatibility must be strictly observed.
Choose deepeval if…
- License: deepeval is Apache-2.0, contextcheck is MIT.
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: evaluation, metrics.
- When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
When NOT to use deepeval
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill.
- In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Addepto/contextcheck) · observed Sep 8, 2026
- GitHub forks (Addepto/contextcheck) · observed Sep 8, 2026
- Last push (Addepto/contextcheck) · observed Dec 11, 2024
- License file (MIT) · observed Sep 8, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (confident-ai/deepeval) · observed Aug 28, 2026
- GitHub forks (confident-ai/deepeval) · observed Aug 28, 2026
- Last push (confident-ai/deepeval) · observed Aug 26, 2026
- License file (Apache-2.0) · observed Aug 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: contextcheck 97 · deepeval 18k (synced Sep 8, 2026).
Common questions
- What is the difference between contextcheck and deepeval?
- contextcheck: Framework for LLMs and RAGs testing in Python. deepeval: LLM Evaluation Framework.. See the comparison table for live GitHub stats and shared categories.
- When should I choose contextcheck over deepeval?
- Choose contextcheck over deepeval when License: contextcheck is MIT, deepeval is Apache-2.0; Tags unique to contextcheck: ai-chat, ai-testing, chatbot-framework, ci-integration; Also covers Model Training; When you require a framework specifically designed to test the robustness of both LLMs and Retrieval-Augmented Generation systems within Python projects.
- When should I choose deepeval over contextcheck?
- Choose deepeval over contextcheck when License: deepeval is Apache-2.0, contextcheck is MIT; Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: evaluation, metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
- When should I avoid contextcheck?
- Avoid if you aim for a framework without configuration flexibility through YAML as contextcheck strictly relies on this format for setting up test environments. Skip contextcheck if your project environment or requirements do not align with the MIT license terms, especially in contexts where licensing compatibility must be strictly observed.
- When should I avoid deepeval?
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
- Is contextcheck or deepeval more popular on GitHub?
- deepeval has more GitHub stars (17,914 vs 97). Stars measure visibility, not whether either tool fits your constraints.
- Are contextcheck and deepeval open source?
- Yes - both are open-source projects on GitHub (contextcheck: MIT, deepeval: Apache-2.0).
- Where can I find alternatives to contextcheck or deepeval?
- GraphCanon lists graph-backed alternatives at contextcheck alternatives and deepeval alternatives (contextcheck markdown twin, deepeval 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, contextcheck or deepeval?
- contextcheck: Dormant. deepeval: Very active. 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 contextcheck and deepeval?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: contextcheck trust report; deepeval trust report.