Comparison
deepeval vs hypertunity
Verdict
Pick deepeval when tags unique to deepeval: llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics, evaluation-framework; pick hypertunity when tags unique to hypertunity: tensorboard, slurm, gpyopt, bayesian-optimization.
Markdown twin · deepeval alternatives · hypertunity alternatives
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Trust & integrity
| Signal | deepeval | hypertunity |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Dormant (2358d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- deepeval
- The LLM Evaluation Framework
- hypertunity
- A toolset for black-box hyperparameter optimisation.
Stars
- deepeval
- 17k
- hypertunity
- 137
Forks
- deepeval
- 1.6k
- hypertunity
- 10
Open issues
- deepeval
- 334
- hypertunity
- 0
Language
- deepeval
- Python
- hypertunity
- Python
Adopt for
- deepeval
- -
- hypertunity
- -
Persona
- deepeval
- -
- hypertunity
- -
Runtime
- deepeval
- -
- hypertunity
- -
License
- deepeval
- Apache-2.0
- hypertunity
- Apache-2.0
Last pushed
- deepeval
- Jul 10, 2026
- hypertunity
- Jan 26, 2020
Categories
- deepeval
- LLM Frameworks, Evaluation & Observability
- hypertunity
- Evaluation & Observability
Trust and health
Maintenance
- deepeval
- Very active (96%)
- hypertunity
- Dormant (18%)
Days since push
- deepeval
- 0d
- hypertunity
- 2358d
Open issues (now)
- deepeval
- 334
- hypertunity
- 0
Owner type
- deepeval
- Organization
- hypertunity
- User
Full report
- deepeval
- Trust report
- hypertunity
- Trust report
Choose deepeval if…
- Tags unique to deepeval: llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics, evaluation-framework.
- Also covers LLM Frameworks.
- More GitHub stars (17k vs 137) - visibility, not fit.
When NOT to use deepeval
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose hypertunity if…
- Tags unique to hypertunity: tensorboard, slurm, gpyopt, bayesian-optimization.
- Leaner open-issue backlog (0).
When NOT to use hypertunity
- Last GitHub push was 2358 days ago (dormant maintenance, Jan 26, 2020). Validate activity before betting a new project on hypertunity.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
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 Jul 11, 2026
- GitHub forks (confident-ai/deepeval) · observed Jul 11, 2026
- Last push (confident-ai/deepeval) · observed Jul 10, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (gdikov/hypertunity) · observed Jul 11, 2026
- GitHub forks (gdikov/hypertunity) · observed Jul 11, 2026
- Last push (gdikov/hypertunity) · observed Jan 26, 2020
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deepeval 17k · hypertunity 137 (synced Jul 11, 2026).
Common questions
- What is the difference between deepeval and hypertunity?
- deepeval: The LLM Evaluation Framework. hypertunity: A toolset for black-box hyperparameter optimisation.. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over hypertunity?
- Choose deepeval over hypertunity when Tags unique to deepeval: llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics, evaluation-framework; Also covers LLM Frameworks; More GitHub stars (17k vs 137) - visibility, not fit.
- When should I choose hypertunity over deepeval?
- Choose hypertunity over deepeval when Tags unique to hypertunity: tensorboard, slurm, gpyopt, bayesian-optimization; Leaner open-issue backlog (0).
- When should I avoid deepeval?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- When should I avoid hypertunity?
- Last GitHub push was 2358 days ago (dormant maintenance, Jan 26, 2020). Validate activity before betting a new project on hypertunity. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- Is deepeval or hypertunity more popular on GitHub?
- deepeval has more GitHub stars (16,767 vs 137). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and hypertunity open source?
- Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, hypertunity: Apache-2.0).
- Where can I find alternatives to deepeval or hypertunity?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and hypertunity alternatives (deepeval markdown twin, hypertunity 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 hypertunity?
- deepeval: Very active. hypertunity: 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 hypertunity?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; hypertunity trust report.