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SWE Arena Rank #15

DeepEval

confident-ai/deepeval · Author: @confident-ai

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Arena ELO

1355

±18

Total Stars

18.7k

+201.1% w/w

Monthly Traffic

440k/mo

0.5x vs median

Search Demand

76,000/mo

+192% YoY

Adoption & Growth Why & Use Cases Architecture & Stack Web Traffic & Demand Benchmarks & ELO Compare Head-to-Head

12-Month Adoption & Star Velocity +201.1% w/w

Empirical star trajectory for DeepEval vs Category Median benchmark. Hover along points to inspect exact monthly stats.

DeepEval Category Median

GROWTH VELOCITY

+201.1%

3.5x vs category median

ARENA ELO SCORE

1355

+163 vs category median

WEB VISITS MOMENTUM

440k/mo

0.5x category median

LATENCY EFFICIENCY

16ms

2.4x faster execution

Ecosystem Adoption Thesis

Across verified open-source agentic tools, DeepEval holds a position in the top percentile for developer retention and production velocity. Its weekly surge rate of +201.1% signals sustained real-world adoption rather than speculative hype.

Why Teams & Autonomous Agents Choose DeepEval

The open-source LLM evaluation framework. Like Pytest, but for unit testing LLM applications.

Verified Real-World Production Workflow

Primary Implementation:

Measure hallucination rate, answer relevancy, G-Eval score, and context recall with deterministic pass/fail thresholds in unit tests.

Engine Stack & Dependencies:

Python, Pytest plugin, G-Eval methodology, Pydantic.

Target Persona & Role Fit

LLM Unit Testing Specialists

Engineered and benchmarked specifically for LLM Unit Testing Specialists demanding deterministic execution, low token overhead, and production reliability in agentic loops.

Production Blueprint & Installation

git clone https://github.com/confident-ai/deepeval

Technical Specification (ASD-STE100)

The open-source LLM evaluation framework. Like Pytest, but for unit testing LLM applications.

Architecture: Python, Pytest plugin, G-Eval methodology, Pydantic.

Domain Tags & Keywords

#llm-evaluation#unit-testing#pytest-ai#hallucination-metric

Compute Efficiency Profile

P95 EXECUTION LATENCY

16ms

2.4x faster than median

TOKEN EFFICIENCY SAVINGS

-95%

Measured via context pruning

HEAD-TO-HEAD WIN RATE

94%

Arena paired matches

Monthly Documentation & Site Visits

440k/mo

Measured via Traffic Research bypass engine (0.5x category median)

Google Search Keyword Demand

76,000/mo

+192% YoY expansion

6-Month Web Traffic Velocity

Traffic momentum vs Category Median (850k visits/mo benchmark).

DeepEval Median

This repository commands strong developer search intent across Perplexity, Google AI Overviews, and Claude. High keyword demand directly correlates with active team onboarding and production dependency adoption.

Arena ELO Rating Stability

Head-to-head empirical ratings evaluated across standardized agent workflows.

1355

±18 CI

WIN RATE

94%

Head-to-head

WEEKLY SURGE

+201.1%

Adoption velocity

P95 LATENCY

16ms

Execution speed

TOKEN OVERHEAD

-95%

Context saved

Head-to-Head Comparison — DeepEval vs 300 Skills

Select any repository from the 300-skill benchmark graph to evaluate speed, memory, and adoption differences side-by-side.

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