DeepEval
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No lifecycle review is recorded for this listing. Its inclusion in the directory does not confirm current availability; check the vendor before relying on it.
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Apache-licensed Python LLM evaluation framework; the Confident AI reporting and tracing platform is separate. No lifecycle review is recorded for this listing. Its inclusion in the directory does not confirm current availability; check the vendor before relying on it.
Product preview
Decision notes
Official-document research
Based on the cited documentation. We did not use the product, purchase a plan, or run quality, speed or reliability tests in this review.
Consider it for
- Python teams maintaining datasets and reviewing metric failures
Choose another approach if
- A metric score used as proof of compliance
- Assuming cloud quotas restrict the free local code
Pricing and conditions
Documented terms
Apache2 framework code has no software royalty; judges, compute and providers can cost separately. Confident Free lists 2 seats, 1 project and 5 test runs/week, plus 1 GB/month traces with excess dropped. Starter lists $200/month and 5 GB/month, then $1/GB/month ingested OR retained. Taxes, ISO currency and account-specific charges remain unconfirmed; cloud caps do not cap local tests.
Pricing source read:
Pricing or terms sourceCode, model and service licensing
Apache2 covers framework code with notice/change obligations. Confident terms allow service processing and a perpetual aggregated-data license; training on Customer Data requires prior written consent, distinct from aggregates and feedback. Inputs, generated test data and outputs still need their own rights. Privacy retention is purpose/legal based, not zero retention; provider rules are separate.
Basis and limits of the recorded score
Original 4.5/5 retained; the original scoring worksheet and hands-on evidence are unavailable. This documentation review did not re-score it.
Overview
DeepEval evaluates application responses, retrieval and agent behavior with test cases and metrics. Many metrics use an LLM judge, so a score depends on the metric, data and judge; it is not a security, copyright or universal quality certification.
The Python framework can be used independently of Confident AI. Logging in enables cloud reports and synchronization; online tracing and shared reports have separate platform limits. Framework telemetry uses PostHog and can be disabled. The documented event payload excludes test results, but optional cloud storage and your model provider are different data paths.
Sources
The factual claims in this review were read from the pages below. Each date is when an editor last opened the source, not when the product changed.
- Vendor documentation Checked 2026-10-15
- Vendor documentation Checked 2026-10-15
- Vendor documentation Checked 2026-10-15
- Vendor documentation Checked 2026-10-15
- Vendor documentation Checked 2026-10-15
- Vendor pricing page Checked 2026-10-15
- Vendor documentation Checked 2026-10-15
- Vendor documentation Checked 2026-10-15
Pros / Cons
Pros
- Evaluation integrated with Python tests
- Documented metrics and cloud/local separation
Cons
- Judge output can vary
- Cloud storage and API bills are separate
Who it's for
A versioned regression dataset
Comparing a bounded application change
Bottom line
Choose representative cases and a judge budget before adding cloud reporting.
Key Features
Tags
Frequently asked questions
Is DeepEval currently available?
No lifecycle review is recorded for this listing. Its inclusion in the directory does not confirm current availability; check the vendor before relying on it.
What is DeepEval?
DeepEval is a Code Generation tool developed by Confident AI. Apache-licensed Python LLM evaluation framework; the Confident AI reporting and tracing platform is separate.
What costs and terms should I check for DeepEval?
Apache2 framework code has no software royalty; judges, compute and providers can cost separately. Confident Free lists 2 seats, 1 project and 5 test runs/week, plus 1 GB/month traces with excess dropped. Starter lists $200/month and 5 GB/month, then $1/GB/month ingested OR retained. Taxes, ISO currency and account-specific charges remain unconfirmed; cloud caps do not cap local tests.
Is DeepEval open source?
Apache2 covers framework code with notice/change obligations. Confident terms allow service processing and a perpetual aggregated-data license; training on Customer Data requires prior written consent, distinct from aggregates and feedback. Inputs, generated test data and outputs still need their own rights. Privacy retention is purpose/legal based, not zero retention; provider rules are separate.
What are the best alternatives to DeepEval?
Notable Code Generation alternatives include GitHub Copilot, Cursor, Replit Agent. Browse all 76 tools in our Code Generation category for a full overview.
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Basic Info
- Pricing
- Freemium
Apache2 framework code has no software royalty; judges, compute and providers can cost separately. Confident Free lists 2 seats, 1 project and 5 test runs/week, plus 1 GB/month traces with excess dropped. Starter lists $200/month and 5 GB/month, then $1/GB/month ingested OR retained. Taxes, ISO currency and account-specific charges remain unconfirmed; cloud caps do not cap local tests.
- Editorial score
- ★ 4.5 / 5 How we score
- Platforms
- LibraryCloud
- Last verified
- Not recorded
