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OpenAI Swarm
STEM Arena Rank #235

OpenAI Swarm

openai/swarm · Author: @openai
Arena ELO
1188
±25
Total Stars
22.0k
+NaN% w/w
Monthly Traffic
650k/mo
0.8x vs median
Search Demand
72,000/mo
+35% (Steady) YoY

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

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

OpenAI Swarm Category Median
22k 13k 3k NovDecJanFebMarAprMayJunJulAugSepOct Nov · 3.4k vs 4.4k med This Skill: 3.4k -960 vs Median Dec · 4.1k vs 5.0k med This Skill: 4.1k -928 vs Median Jan · 4.8k vs 5.7k med This Skill: 4.8k -861 vs Median Feb · 5.7k vs 6.5k med This Skill: 5.7k -751 vs Median Mar · 6.8k vs 7.3k med This Skill: 6.8k -583 vs Median Apr · 8.0k vs 8.4k med This Skill: 8.0k -343 vs Median May · 9.5k vs 9.5k med This Skill: 9.5k -11 vs Median Jun · 11.2k vs 10.8k med This Skill: 11.2k +435 vs Median Jul · 13.3k vs 12.3k med This Skill: 13.3k +1.0k vs Median Aug · 15.7k vs 13.9k med This Skill: 15.7k +1.8k vs Median Sep · 18.6k vs 15.8k med This Skill: 18.6k +2.8k vs Median Oct · 22.0k vs 18.0k med This Skill: 22.0k +4.0k vs Median
GROWTH VELOCITY
+NaN%
1.2x vs category median
ARENA ELO SCORE
1188
-4 vs category median
WEB VISITS MOMENTUM
650k/mo
0.8x category median
LATENCY EFFICIENCY
55ms
0.7x faster execution

Ecosystem Adoption Thesis

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

Why Teams & Autonomous Agents Choose OpenAI Swarm

Ergonomic educational framework for multi-agent orchestration, agent handoffs, and deterministic routine composition.

Verified Real-World Production Workflow

Primary Implementation:

Studying and prototyping lightweight multi-agent delegation patterns with transparent Python code and minimal abstractions.

Engine Stack & Dependencies:

Python, Stateless agent functions, OpenAI Chat Completions tool calling.

Target Persona & Role Fit

Multi-Agent Researchers

Engineered and benchmarked specifically for Multi-Agent Researchers demanding deterministic execution, low token overhead, and production reliability in agentic loops.

Production Blueprint & Installation

git clone https://github.com/openai/swarm

Technical Specification (ASD-STE100)

Ergonomic educational framework for multi-agent orchestration, agent handoffs, and deterministic routine composition.
Architecture: Python, Stateless agent functions, OpenAI Chat Completions tool calling.

Domain Tags & Keywords

#Multi-Agent#Agent Handoffs#OpenAI#Routines#Coordination

Compute Efficiency Profile

P95 EXECUTION LATENCY
55ms
0.7x faster than median
TOKEN EFFICIENCY SAVINGS
-40%
Measured via context pruning
HEAD-TO-HEAD WIN RATE
71%
Arena paired matches
Monthly Documentation & Site Visits
650k/mo
Measured via Traffic Research bypass engine (0.8x category median)
Google Search Keyword Demand
72,000/mo
+35% (Steady) YoY expansion

6-Month Web Traffic Velocity

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

OpenAI Swarm Median
850k 584k 319k MayJunJulAugSepOct May · 318.5k vs 680.0k med This Skill: 318.5k -361.5k vs Median Jun · 384.8k vs 714.0k med This Skill: 384.8k -329.2k vs Median Jul · 451.1k vs 748.0k med This Skill: 451.1k -296.9k vs Median Aug · 517.4k vs 782.0k med This Skill: 517.4k -264.6k vs Median Sep · 583.7k vs 816.0k med This Skill: 583.7k -232.3k vs Median Oct · 650.0k vs 850.0k med This Skill: 650.0k -200.0k 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.

1188
±25 CI
1k 1k 1k MayJunJulAugSepOct May · 1.2k vs 1.2k med This Skill: 1.2k -29 vs Median Jun · 1.2k vs 1.2k med This Skill: 1.2k -23 vs Median Jul · 1.2k vs 1.2k med This Skill: 1.2k -9 vs Median Aug · 1.2k vs 1.2k med This Skill: 1.2k +2 vs Median Sep · 1.2k vs 1.2k med This Skill: 1.2k +1 vs Median Oct · 1.2k vs 1.2k med This Skill: 1.2k -10 vs Median
WIN RATE
71%
Head-to-head
WEEKLY SURGE
+NaN%
Adoption velocity
P95 LATENCY
55ms
Execution speed
TOKEN OVERHEAD
-40%
Context saved

Head-to-Head Comparison — OpenAI Swarm 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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