Home/Compare/deepeval vs instruct-eval

Comparison

deepeval vs instruct-eval

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 instruct-eval if key facts about instruct-eval.

Markdown twin · deepeval alternatives · instruct-eval alternatives

GraphCanon updated 2w

deepeval logo

deepeval

confident-ai/deepeval

17kpushed Jul 27, 2026
vs
instruct-eval logo

instruct-eval

declare-lab/instruct-eval

552pushed Mar 10, 2024

Trust & integrity

Signaldeepevalinstruct-eval
Maintenance
Very active (1d since push)
As of 4w · github_public_v1
Dormant (879d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 4w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
Published findings
As of 1mo · 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.
instruct-eval
Quantitative evaluation for instruction-tuned language models

Stars

deepeval
17k
instruct-eval
552

Forks

deepeval
1.7k
instruct-eval
45

Open issues

deepeval
404
instruct-eval
24

Language

deepeval
Python
instruct-eval
Python

Adopt for

deepeval
Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
instruct-eval
Key facts about instruct-eval

Persona

deepeval
-
instruct-eval
-

Runtime

deepeval
-
instruct-eval
-

License

deepeval
Apache-2.0 License
instruct-eval
The tool is distributed under Apache-2.0 license

Last pushed

deepeval
Jul 27, 2026
instruct-eval
Mar 10, 2024

Categories

deepeval
Evaluation & Observability
instruct-eval
Evaluation & Observability

Trust and health

Maintenance

deepeval
Very active (96%)
instruct-eval
Dormant (18%)

Days since push

deepeval
1d
instruct-eval
879d

Open issues (now)

deepeval
404
instruct-eval
24

OSV dependency advisories

deepeval
No lockfile (source not queried)
instruct-eval
Published findings

Full report

deepeval
Trust report
instruct-eval
Trust report

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 instruct-eval if…

  • Requirements: Min 8 GB RAM; Requires Python environment setup and specific dependencies as outlined in the repository's documentation..
  • Tags unique to instruct-eval: benchmarking, instruct-tuning, llm, safety.
  • When you need to quantitatively evaluate the performance of instruction-tuned large language models such as Alpaca and Flan-T5 on held-out tasks.

When NOT to use instruct-eval

  • When primarily interested in general model evaluation without a focus on instruction-tuned LMs.
  • If your primary interest lies in qualitative assessment rather than quantitative metrics.
  • If you need support for non-HuggingFace Transformer models, as instruct-eval mainly supports models from the HuggingFace ecosystem.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: deepeval 17k · instruct-eval 552 (synced Jul 28, 2026).

Common questions

What is the difference between deepeval and instruct-eval?
deepeval: LLM Evaluation Framework.. instruct-eval: Quantitative evaluation for instruction-tuned language models. See the comparison table for live GitHub stats and shared categories.
When should I choose deepeval over instruct-eval?
Choose deepeval over instruct-eval 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 instruct-eval over deepeval?
Choose instruct-eval over deepeval when Requirements: Min 8 GB RAM; Requires Python environment setup and specific dependencies as outlined in the repository's documentation.; Tags unique to instruct-eval: benchmarking, instruct-tuning, llm, safety; When you need to quantitatively evaluate the performance of instruction-tuned large language models such as Alpaca and Flan-T5 on held-out tasks.
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 instruct-eval?
When primarily interested in general model evaluation without a focus on instruction-tuned LMs. If your primary interest lies in qualitative assessment rather than quantitative metrics. If you need support for non-HuggingFace Transformer models, as instruct-eval mainly supports models from the HuggingFace ecosystem.
Is deepeval or instruct-eval more popular on GitHub?
deepeval has more GitHub stars (17,226 vs 552). Stars measure visibility, not whether either tool fits your constraints.
Are deepeval and instruct-eval open source?
Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, instruct-eval: Apache-2.0).
Where can I find alternatives to deepeval or instruct-eval?
GraphCanon lists graph-backed alternatives at deepeval alternatives and instruct-eval alternatives (deepeval markdown twin, instruct-eval 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 instruct-eval?
deepeval: Very active. instruct-eval: 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 instruct-eval?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; instruct-eval trust report.

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