Home/Compare/deepeval vs awesome-tensor-compilers

Comparison

deepeval vs awesome-tensor-compilers

Verdict

Pick deepeval when tags unique to deepeval: python, llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics; pick awesome-tensor-compilers when tags unique to awesome-tensor-compilers: deep-learning, high-performance-computing, compiler, machine-learning.

Markdown twin · deepeval alternatives · awesome-tensor-compilers alternatives

GraphCanon updated today

deepeval logo

deepeval

confident-ai/deepeval

17kpushed Jul 10, 2026
vs
awesome-tensor-compilers logo

awesome-tensor-compilers

merrymercy/awesome-tensor-compilers

2.8kpushed Oct 19, 2024

Trust & integrity

Signaldeepevalawesome-tensor-compilers
Maintenance
Very active (0d since push)
As of today · github_public_v1
Dormant (630d 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
awesome-tensor-compilers
A list of awesome compiler projects and papers for tensor computation and deep learning.

Stars

deepeval
17k
awesome-tensor-compilers
2.8k

Forks

deepeval
1.6k
awesome-tensor-compilers
327

Open issues

deepeval
334
awesome-tensor-compilers
4

Language

deepeval
Python
awesome-tensor-compilers
-

Adopt for

deepeval
-
awesome-tensor-compilers
-

Persona

deepeval
-
awesome-tensor-compilers
-

Runtime

deepeval
-
awesome-tensor-compilers
-

License

deepeval
Apache-2.0
awesome-tensor-compilers
-

Last pushed

deepeval
Jul 10, 2026
awesome-tensor-compilers
Oct 19, 2024

Categories

deepeval
LLM Frameworks, Evaluation & Observability
awesome-tensor-compilers
Evaluation & Observability

Trust and health

Maintenance

deepeval
Very active (96%)
awesome-tensor-compilers
Dormant (18%)

Days since push

deepeval
0d
awesome-tensor-compilers
630d

Open issues (now)

deepeval
334
awesome-tensor-compilers
4

Owner type

deepeval
Organization
awesome-tensor-compilers
User

Full report

deepeval
Trust report
awesome-tensor-compilers
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 2.8k) - 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 awesome-tensor-compilers if…

  • Tags unique to awesome-tensor-compilers: deep-learning, high-performance-computing, compiler, machine-learning.
  • Leaner open-issue backlog (4).

When NOT to use awesome-tensor-compilers

  • Last GitHub push was 630 days ago (dormant maintenance, Oct 19, 2024). Validate activity before betting a new project on awesome-tensor-compilers.
  • 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 on cards: deepeval 17k · awesome-tensor-compilers 2.8k (synced Jul 11, 2026).

Common questions

What is the difference between deepeval and awesome-tensor-compilers?
deepeval: The LLM Evaluation Framework. awesome-tensor-compilers: A list of awesome compiler projects and papers for tensor computation and deep learning.. See the comparison table for live GitHub stats and shared categories.
When should I choose deepeval over awesome-tensor-compilers?
Choose deepeval over awesome-tensor-compilers when Tags unique to deepeval: python, llm-evaluation-framework, evaluation-metrics, llm-evaluation-metrics; Also covers LLM Frameworks; More GitHub stars (17k vs 2.8k) - visibility, not fit.
When should I choose awesome-tensor-compilers over deepeval?
Choose awesome-tensor-compilers over deepeval when Tags unique to awesome-tensor-compilers: deep-learning, high-performance-computing, compiler, machine-learning; Leaner open-issue backlog (4).
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 awesome-tensor-compilers?
Last GitHub push was 630 days ago (dormant maintenance, Oct 19, 2024). Validate activity before betting a new project on awesome-tensor-compilers. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Is deepeval or awesome-tensor-compilers more popular on GitHub?
deepeval has more GitHub stars (16,767 vs 2,762). Stars measure visibility, not whether either tool fits your constraints.
Are deepeval and awesome-tensor-compilers open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to deepeval or awesome-tensor-compilers?
GraphCanon lists graph-backed alternatives at deepeval alternatives and awesome-tensor-compilers alternatives (deepeval markdown twin, awesome-tensor-compilers 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 awesome-tensor-compilers?
deepeval: Very active. awesome-tensor-compilers: 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 awesome-tensor-compilers?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; awesome-tensor-compilers trust report.