Comparison
deepeval vs uptrain
Verdict
Pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies; pick uptrain if upTrain, an open-source platform, evaluates and enhances Generative AI applications with preconfigured checks, root cause analysis, and actionable insights.
Markdown twin · deepeval alternatives · uptrain alternatives
GraphCanon updated Sep 20, 2026
11views this month
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Trust & integrity
| Signal | deepeval | uptrain |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (762d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 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
- deepeval
- LLM Evaluation Framework.
- uptrain
- Unified platform for evaluating and improving Generative AI applications
Stars
- deepeval
- 18k
- uptrain
- 2.4k
Forks
- deepeval
- 2.0k
- uptrain
- 205
Open issues
- deepeval
- 624
- uptrain
- 65
Language
- deepeval
- Python
- uptrain
- Python
Adopt for
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- uptrain
- UpTrain, an open-source platform, evaluates and enhances Generative AI applications with preconfigured checks, root cause analysis, and actionable insights.
Persona
- deepeval
- -
- uptrain
- -
Runtime
- deepeval
- -
- uptrain
- -
License
- deepeval
- Apache-2.0 License
- uptrain
- The tool is available under the Apache-2.0 license, suitable for both free and commercial use with appropriate attribution.
Last pushed
- deepeval
- Sep 18, 2026
- uptrain
- Aug 18, 2024
Categories
- deepeval
- Evaluation & Observability
- uptrain
- Evaluation & Observability
Trust and health
Maintenance
- deepeval
- Very active (96%)
- uptrain
- Dormant (18%)
Days since push
- deepeval
- 1d
- uptrain
- 762d
Open issues (now)
- deepeval
- 624
- uptrain
- 65
Stars delta
- deepeval
- +1.1k (30d)
- uptrain
- +6 (30d)
Open issues delta
- deepeval
- +220 (30d)
- uptrain
- +7 (30d)
Full report
- deepeval
- Trust report
- uptrain
- Trust report
Shared compatibility
- Python · deepeval: Python runtime · uptrain: Python runtime
Choose deepeval if…
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: llm-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.
Choose uptrain if…
- UpTrain can be installed on-premises using pip or accessed through a managed version.
- Tags unique to uptrain: autoevaluation, experimentation, hallucination-detection, jailbreak-detection.
- uptrain ships Docker support for self-hosted deployment.
- - When you need to evaluate Generative AI applications across various use-cases including language models, code generation, and embeddings.
When NOT to use uptrain
- - When your application does not require extensive monitoring or do not need insights into improving Generative AI performance through root cause analysis.
- - If you prioritize a highly hands-off user experience without the capability to customize evaluation checks, consider using UpTrain's managed version instead of self-managing it.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (confident-ai/deepeval) · observed Sep 20, 2026
- GitHub forks (confident-ai/deepeval) · observed Sep 20, 2026
- Last push (confident-ai/deepeval) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (uptrain-ai/uptrain) · observed Sep 20, 2026
- GitHub forks (uptrain-ai/uptrain) · observed Sep 20, 2026
- Last push (uptrain-ai/uptrain) · observed Aug 18, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deepeval 18k · uptrain 2.4k (synced Sep 20, 2026).
Common questions
- What is the difference between deepeval and uptrain?
- deepeval: LLM Evaluation Framework.. uptrain: Unified platform for evaluating and improving Generative AI applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over uptrain?
- Choose deepeval over uptrain when Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: llm-evaluation, metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
- When should I choose uptrain over deepeval?
- Choose uptrain over deepeval when UpTrain can be installed on-premises using pip or accessed through a managed version; Tags unique to uptrain: autoevaluation, experimentation, hallucination-detection, jailbreak-detection; uptrain ships Docker support for self-hosted deployment; - When you need to evaluate Generative AI applications across various use-cases including language models, code generation, and embeddings.
- 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.
- When should I avoid uptrain?
- - When your application does not require extensive monitoring or do not need insights into improving Generative AI performance through root cause analysis. - If you prioritize a highly hands-off user experience without the capability to customize evaluation checks, consider using UpTrain's managed version instead of self-managing it.
- Is deepeval or uptrain more popular on GitHub?
- deepeval has more GitHub stars (18,342 vs 2,365). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and uptrain open source?
- Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, uptrain: Apache-2.0).
- Where can I find alternatives to deepeval or uptrain?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and uptrain alternatives (deepeval markdown twin, uptrain 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, deepeval or uptrain?
- deepeval: Very active. uptrain: 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 deepeval and uptrain?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; uptrain trust report.