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RAGFlow
Founders & Solo Creators Arena Rank #48

RAGFlow

infiniflow/ragflow · Author: @infiniflow
Arena ELO
1315
±16
Total Stars
91.8k
+182.3% w/w
Monthly Traffic
850k/mo
1.0x vs median
Search Demand
140,000/mo
+190% YoY

12-Month Adoption & Star Velocity +182.3% w/w

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

RAGFlow Category Median
92k 46k 1k NovDecJanFebMarAprMayJunJulAugSepOct Nov · 1.2k vs 4.4k med This Skill: 1.2k -3.2k vs Median Dec · 1.8k vs 5.0k med This Skill: 1.8k -3.2k vs Median Jan · 2.7k vs 5.7k med This Skill: 2.7k -3.0k vs Median Feb · 4.0k vs 6.5k med This Skill: 4.0k -2.5k vs Median Mar · 5.9k vs 7.3k med This Skill: 5.9k -1.5k vs Median Apr · 8.7k vs 8.4k med This Skill: 8.7k +378 vs Median May · 12.9k vs 9.5k med This Skill: 12.9k +3.4k vs Median Jun · 19.1k vs 10.8k med This Skill: 19.1k +8.3k vs Median Jul · 28.3k vs 12.3k med This Skill: 28.3k +16.0k vs Median Aug · 41.9k vs 13.9k med This Skill: 41.9k +28.0k vs Median Sep · 62.0k vs 15.8k med This Skill: 62.0k +46.2k vs Median Oct · 91.8k vs 18.0k med This Skill: 91.8k +73.8k vs Median
GROWTH VELOCITY
+182.3%
2.8x vs category median
ARENA ELO SCORE
1315
+123 vs category median
WEB VISITS MOMENTUM
850k/mo
1.0x category median
LATENCY EFFICIENCY
35ms
1.1x faster execution

Ecosystem Adoption Thesis

Across verified open-source agentic tools, RAGFlow holds a position in the top percentile for developer retention and production velocity. Its weekly surge rate of +182.3% signals sustained real-world adoption rather than speculative hype.

Why Teams & Autonomous Agents Choose RAGFlow

Open-source RAG engine based on deep document understanding with fine-grained chunking templates.

Verified Real-World Production Workflow

Primary Implementation:

Extract structured intelligence from complex PDFs, Excel sheets, and slides with zero hallucinations.

Engine Stack & Dependencies:

Python, DeepDoc OCR, Elasticsearch, Infinity tensor engine.

Target Persona & Role Fit

Full-Stack AI Engineers

Engineered and benchmarked specifically for Full-Stack AI Engineers demanding deterministic execution, low token overhead, and production reliability in agentic loops.

Production Blueprint & Installation

git clone https://github.com/infiniflow/ragflow

Technical Specification (ASD-STE100)

Open-source RAG engine based on deep document understanding with fine-grained chunking templates.
Architecture: Python, DeepDoc OCR, Elasticsearch, Infinity tensor engine.

Domain Tags & Keywords

#rag#deepdoc#document-ai#retrieval

Compute Efficiency Profile

P95 EXECUTION LATENCY
35ms
1.1x faster than median
TOKEN EFFICIENCY SAVINGS
-88%
Measured via context pruning
HEAD-TO-HEAD WIN RATE
88%
Arena paired matches
Monthly Documentation & Site Visits
850k/mo
Measured via Traffic Research bypass engine (1.0x category median)
Google Search Keyword Demand
140,000/mo
+190% YoY expansion

6-Month Web Traffic Velocity

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

RAGFlow Median
850k 489k 128k MayJunJulAugSepOct May · 127.5k vs 680.0k med This Skill: 127.5k -552.5k vs Median Jun · 127.5k vs 714.0k med This Skill: 127.5k -586.5k vs Median Jul · 260.9k vs 748.0k med This Skill: 260.9k -487.1k vs Median Aug · 457.3k vs 782.0k med This Skill: 457.3k -324.7k vs Median Sep · 653.6k vs 816.0k med This Skill: 653.6k -162.3k vs Median Oct · 850.0k vs 850.0k med This Skill: 850.0k +0 vs 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.

1315
±16 CI
1k 1k 1k MayJunJulAugSepOct May · 1.3k vs 1.2k med This Skill: 1.3k +98 vs Median Jun · 1.3k vs 1.2k med This Skill: 1.3k +104 vs Median Jul · 1.3k vs 1.2k med This Skill: 1.3k +118 vs Median Aug · 1.3k vs 1.2k med This Skill: 1.3k +129 vs Median Sep · 1.3k vs 1.2k med This Skill: 1.3k +128 vs Median Oct · 1.3k vs 1.2k med This Skill: 1.3k +117 vs Median
WIN RATE
88%
Head-to-head
WEEKLY SURGE
+182.3%
Adoption velocity
P95 LATENCY
35ms
Execution speed
TOKEN OVERHEAD
-88%
Context saved

Head-to-Head Comparison — RAGFlow 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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