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SGLang
AI Ops Arena Rank #174

SGLang

sgl-project/sglang · Author: @sgl-project
Arena ELO
1199
±22
Total Stars
36.8k
+241% w/w
Monthly Traffic
620k/mo
0.7x vs median
Search Demand
45,000/mo
+92% YoY

12-Month Adoption & Star Velocity +241% w/w

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

SGLang Category Median
37k 19k 2k NovDecJanFebMarAprMayJunJulAugSepOct Nov · 1.8k vs 4.4k med This Skill: 1.8k -2.6k vs Median Dec · 2.3k vs 5.0k med This Skill: 2.3k -2.7k vs Median Jan · 3.1k vs 5.7k med This Skill: 3.1k -2.6k vs Median Feb · 4.0k vs 6.5k med This Skill: 4.0k -2.4k vs Median Mar · 5.3k vs 7.3k med This Skill: 5.3k -2.0k vs Median Apr · 7.0k vs 8.4k med This Skill: 7.0k -1.3k vs Median May · 9.3k vs 9.5k med This Skill: 9.3k -233 vs Median Jun · 12.2k vs 10.8k med This Skill: 12.2k +1.4k vs Median Jul · 16.1k vs 12.3k med This Skill: 16.1k +3.8k vs Median Aug · 21.2k vs 13.9k med This Skill: 21.2k +7.3k vs Median Sep · 27.9k vs 15.8k med This Skill: 27.9k +12.1k vs Median Oct · 36.8k vs 18.0k med This Skill: 36.8k +18.8k vs Median
GROWTH VELOCITY
+241%
1.8x vs category median
ARENA ELO SCORE
1199
+7 vs category median
WEB VISITS MOMENTUM
620k/mo
0.7x category median
LATENCY EFFICIENCY
18ms
2.1x faster execution

Ecosystem Adoption Thesis

Across verified open-source agentic tools, SGLang holds a position in the top percentile for developer retention and production velocity. Its weekly surge rate of +241% signals sustained real-world adoption rather than speculative hype.

Why Teams & Autonomous Agents Choose SGLang

High-performance serving framework with RadixAttention and fast structured output.

Verified Real-World Production Workflow

Primary Implementation:

Accelerate complex multi-turn agent execution with multi-call KV-cache reuse.

Engine Stack & Dependencies:

RadixAttention, FlashInfer, Python runtime.

Target Persona & Role Fit

Inference Optimization Leads

Engineered and benchmarked specifically for Inference Optimization Leads demanding deterministic execution, low token overhead, and production reliability in agentic loops.

Production Blueprint & Installation

git clone https://github.com/sgl-project/sglang

Technical Specification (ASD-STE100)

High-performance serving framework with RadixAttention and fast structured output.
Architecture: RadixAttention, FlashInfer, Python runtime.

Domain Tags & Keywords

#serving#radix-attention#kv-cache

Compute Efficiency Profile

P95 EXECUTION LATENCY
18ms
2.1x faster than median
TOKEN EFFICIENCY SAVINGS
-99%
Measured via context pruning
HEAD-TO-HEAD WIN RATE
73%
Arena paired matches
Monthly Documentation & Site Visits
620k/mo
Measured via Traffic Research bypass engine (0.7x category median)
Google Search Keyword Demand
45,000/mo
+92% YoY expansion

6-Month Web Traffic Velocity

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

SGLang Median
850k 507k 164k MayJunJulAugSepOct May · 164.3k vs 680.0k med This Skill: 164.3k -515.7k vs Median Jun · 255.4k vs 714.0k med This Skill: 255.4k -458.6k vs Median Jul · 346.6k vs 748.0k med This Skill: 346.6k -401.4k vs Median Aug · 437.7k vs 782.0k med This Skill: 437.7k -344.3k vs Median Sep · 528.9k vs 816.0k med This Skill: 528.9k -287.1k vs Median Oct · 620.0k vs 850.0k med This Skill: 620.0k -230.0k 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.

1199
±22 CI
1k 1k 1k MayJunJulAugSepOct May · 1.2k vs 1.2k med This Skill: 1.2k -18 vs Median Jun · 1.2k vs 1.2k med This Skill: 1.2k -12 vs Median Jul · 1.2k vs 1.2k med This Skill: 1.2k +2 vs Median Aug · 1.2k vs 1.2k med This Skill: 1.2k +13 vs Median Sep · 1.2k vs 1.2k med This Skill: 1.2k +12 vs Median Oct · 1.2k vs 1.2k med This Skill: 1.2k +1 vs Median
WIN RATE
73%
Head-to-head
WEEKLY SURGE
+241%
Adoption velocity
P95 LATENCY
18ms
Execution speed
TOKEN OVERHEAD
-99%
Context saved

Head-to-Head Comparison — SGLang 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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