Home/Compare/deepeval vs BIG-bench

Comparison

deepeval vs BIG-bench

Verdict

Pick deepeval when tags unique to deepeval: python, llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics; pick BIG-bench when requirements: Python 3.5-3.8 required.; `pytest` is necessary for running automated tests..

Markdown twin · deepeval alternatives · BIG-bench alternatives

GraphCanon updated today

deepeval logo

deepeval

confident-ai/deepeval

17kpushed Jul 10, 2026
vs
BIG-bench logo

BIG-bench

google/BIG-bench

3.2kpushed Jul 19, 2024

Trust & integrity

SignaldeepevalBIG-bench
Maintenance
Very active (0d since push)
As of today · github_public_v1
Archived (722d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
324 low (324 low)
As of today · osv@v1

Tagline

deepeval
The LLM Evaluation Framework
BIG-bench
Collaborative benchmark for language model capabilities

Stars

deepeval
17k
BIG-bench
3.2k

Forks

deepeval
1.6k
BIG-bench
615

Open issues

deepeval
334
BIG-bench
106

Language

deepeval
Python
BIG-bench
Python

Adopt for

deepeval
-
BIG-bench
Decision-critical facts for BIG-bench

Persona

deepeval
-
BIG-bench
-

Runtime

deepeval
-
BIG-bench
-

License

deepeval
Apache-2.0
BIG-bench
Apache-2.0

Last pushed

deepeval
Jul 10, 2026
BIG-bench
Jul 19, 2024

Categories

deepeval
LLM Frameworks, Evaluation & Observability
BIG-bench
Evaluation & Observability

Trust and health

Maintenance

deepeval
Very active (96%)
BIG-bench
Archived (8%)

Days since push

deepeval
0d
BIG-bench
722d

Archived on GitHub

deepeval
No
BIG-bench
Yes

Open issues (now)

deepeval
334
BIG-bench
106

Security scan

deepeval
No lockfile
BIG-bench
324 low (324 low)

Full report

deepeval
Trust report
BIG-bench
Trust report

Choose deepeval if…

  • Tags unique to deepeval: python, llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics.
  • Also covers LLM Frameworks.
  • More GitHub stars (17k vs 3.2k) - 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 BIG-bench if…

  • Requirements: Python 3.5-3.8 required.; `pytest` is necessary for running automated tests..
  • Tags unique to BIG-bench: tasks creation, evaluation, seqio, language-models.
  • When you need a comprehensive benchmark that evaluates language models across various tasks and includes methods for extrapolating model capabilities.

When NOT to use BIG-bench

  • If you are looking for a tool that simplifies benchmarking with minimal configuration, BIG-bench requires setting up an environment and can be more complex compared to streamlined benchmark tools.
  • As BIG-bench relies on collaboration across various tasks and contributions from the community, it might not be ideal if you need benchmark tasks or evaluations immediately available without potential
  • If your project does not require advanced extrapolation techniques for measuring model capabilities over a wide range of benchmarks, simpler evaluation tools may suffice.

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 · BIG-bench 3.2k (synced Jul 11, 2026).

Common questions

What is the difference between deepeval and BIG-bench?
deepeval: The LLM Evaluation Framework. BIG-bench: Collaborative benchmark for language model capabilities. See the comparison table for live GitHub stats and shared categories.
When should I choose deepeval over BIG-bench?
Choose deepeval over BIG-bench when Tags unique to deepeval: python, llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics; Also covers LLM Frameworks; More GitHub stars (17k vs 3.2k) - visibility, not fit.
When should I choose BIG-bench over deepeval?
Choose BIG-bench over deepeval when Requirements: Python 3.5-3.8 required.; pytest is necessary for running automated tests.; Tags unique to BIG-bench: tasks creation, evaluation, seqio, language-models; When you need a comprehensive benchmark that evaluates language models across various tasks and includes methods for extrapolating model capabilities.
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 BIG-bench?
If you are looking for a tool that simplifies benchmarking with minimal configuration, BIG-bench requires setting up an environment and can be more complex compared to streamlined benchmark tools. As BIG-bench relies on collaboration across various tasks and contributions from the community, it might not be ideal if you need benchmark tasks or evaluations immediately available without potential If your project does not require advanced extrapolation techniques for measuring model capabilities over a wide range of benchmarks, simpler evaluation tools may suffice.
Is deepeval or BIG-bench more popular on GitHub?
deepeval has more GitHub stars (16,767 vs 3,248). Stars measure visibility, not whether either tool fits your constraints.
Are deepeval and BIG-bench open source?
Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, BIG-bench: Apache-2.0).
Where can I find alternatives to deepeval or BIG-bench?
GraphCanon lists graph-backed alternatives at deepeval alternatives and BIG-bench alternatives (deepeval markdown twin, BIG-bench 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 BIG-bench?
deepeval: Very active. BIG-bench: Archived. 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 BIG-bench?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; BIG-bench trust report.