Comparison
deepeval vs ragtune
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 ragtune if ragtune is a command-line tool for evaluating and optimizing retrieval-augmented generation systems, supporting various vector databases and embedding models.
Markdown twin · deepeval alternatives · ragtune alternatives
GraphCanon updated Sep 20, 2026
7views this month
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Trust & integrity
| Signal | deepeval | ragtune |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (176d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- deepeval
- LLM Evaluation Framework.
- ragtune
- Tools for inspecting, debugging, benchmarking, and tuning RAG retrieval
Stars
- deepeval
- 18k
- ragtune
- 13
Forks
- deepeval
- 2.0k
- ragtune
- 1
Open issues
- deepeval
- 624
- ragtune
- 0
Language
- deepeval
- Python
- ragtune
- Go
Adopt for
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- ragtune
- Ragtune is a command-line tool for evaluating and optimizing retrieval-augmented generation systems, supporting various vector databases and embedding models.
Persona
- deepeval
- -
- ragtune
- -
Runtime
- deepeval
- -
- ragtune
- -
License
- deepeval
- Apache-2.0 License
- ragtune
- MIT License
Last pushed
- deepeval
- Sep 18, 2026
- ragtune
- Mar 25, 2026
Categories
- deepeval
- Evaluation & Observability
- ragtune
- Developer Tools, Evaluation & Observability
Trust and health
Maintenance
- deepeval
- Very active (96%)
- ragtune
- Slowing (36%)
Days since push
- deepeval
- 1d
- ragtune
- 176d
Open issues (now)
- deepeval
- 624
- ragtune
- 0
Stars delta
- deepeval
- +1.1k (30d)
- ragtune
- 0 (30d)
Open issues delta
- deepeval
- +220 (30d)
- ragtune
- 0 (30d)
Owner type
- deepeval
- Organization
- ragtune
- User
OSV dependency advisories
- deepeval
- No lockfile (source not queried)
- ragtune
- Published findings
Full report
- deepeval
- Trust report
- ragtune
- Trust report
Choose deepeval if…
- deepeval is primarily Python; ragtune is Go.
- License: deepeval is Apache-2.0, ragtune is MIT.
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: evaluation, llm-evaluation.
- 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 ragtune if…
- ragtune is primarily Go; deepeval is Python.
- License: ragtune is MIT, deepeval is Apache-2.0.
- Pricing: Free and open-source under the MIT License..
- Requirements: Min 2 GB RAM; Go installation is required to use Ragtune..
- Tags unique to ragtune: benchmarking, chroma, cli, embeddings.
- Also covers Developer Tools.
- When you need to inspect, debug, benchmark, and tune the retrieval layer of your RAG systems specifically.
When NOT to use ragtune
- If your project does not involve retrieval-augmented generation systems or if you are not using supported vector databases.
- When you prefer a tool that is not written in Go or does not offer command-line interface capabilities.
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 (metawake/ragtune) · observed Sep 20, 2026
- GitHub forks (metawake/ragtune) · observed Sep 20, 2026
- Last push (metawake/ragtune) · observed Mar 25, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: deepeval 18k · ragtune 13 (synced Sep 20, 2026).
Common questions
- What is the difference between deepeval and ragtune?
- deepeval: LLM Evaluation Framework.. ragtune: Tools for inspecting, debugging, benchmarking, and tuning RAG retrieval. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over ragtune?
- Choose deepeval over ragtune when deepeval is primarily Python; ragtune is Go; License: deepeval is Apache-2.0, ragtune is MIT; Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: evaluation, llm-evaluation; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
- When should I choose ragtune over deepeval?
- Choose ragtune over deepeval when ragtune is primarily Go; deepeval is Python; License: ragtune is MIT, deepeval is Apache-2.0; Pricing: Free and open-source under the MIT License.; Requirements: Min 2 GB RAM; Go installation is required to use Ragtune.; Tags unique to ragtune: benchmarking, chroma, cli, embeddings; Also covers Developer Tools; When you need to inspect, debug, benchmark, and tune the retrieval layer of your RAG systems specifically.
- 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 ragtune?
- If your project does not involve retrieval-augmented generation systems or if you are not using supported vector databases. When you prefer a tool that is not written in Go or does not offer command-line interface capabilities.
- Is deepeval or ragtune more popular on GitHub?
- deepeval has more GitHub stars (18,342 vs 13). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and ragtune open source?
- Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, ragtune: MIT).
- Where can I find alternatives to deepeval or ragtune?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and ragtune alternatives (deepeval markdown twin, ragtune 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 ragtune?
- deepeval: Very active. ragtune: Slowing. 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 ragtune?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; ragtune trust report.