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LiteLLM
AI Ops Arena Rank #229

LiteLLM

BerriAI/litellm · Author: @BerriAI
Arena ELO
1192
±18
Total Stars
60.3k
+227.5% w/w
Monthly Traffic
920k/mo
1.1x vs median
Search Demand
88,000/mo
+68% YoY

12-Month Adoption & Star Velocity +227.5% w/w

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

LiteLLM Category Median
60k 32k 4k NovDecJanFebMarAprMayJunJulAugSepOct Nov · 6.3k vs 4.4k med This Skill: 6.3k +1.8k vs Median Dec · 7.7k vs 5.0k med This Skill: 7.7k +2.7k vs Median Jan · 9.4k vs 5.7k med This Skill: 9.4k +3.7k vs Median Feb · 11.6k vs 6.5k med This Skill: 11.6k +5.1k vs Median Mar · 14.2k vs 7.3k med This Skill: 14.2k +6.9k vs Median Apr · 17.5k vs 8.4k med This Skill: 17.5k +9.2k vs Median May · 21.5k vs 9.5k med This Skill: 21.5k +12.0k vs Median Jun · 26.4k vs 10.8k med This Skill: 26.4k +15.6k vs Median Jul · 32.5k vs 12.3k med This Skill: 32.5k +20.2k vs Median Aug · 39.9k vs 13.9k med This Skill: 39.9k +26.0k vs Median Sep · 49.0k vs 15.8k med This Skill: 49.0k +33.2k vs Median Oct · 60.3k vs 18.0k med This Skill: 60.3k +42.3k vs Median
GROWTH VELOCITY
+227.5%
1.3x vs category median
ARENA ELO SCORE
1192
+0 vs category median
WEB VISITS MOMENTUM
920k/mo
1.1x category median
LATENCY EFFICIENCY
28ms
1.4x faster execution

Ecosystem Adoption Thesis

Across verified open-source agentic tools, LiteLLM holds a position in the top percentile for developer retention and production velocity. Its weekly surge rate of +227.5% signals sustained real-world adoption rather than speculative hype.

Why Teams & Autonomous Agents Choose LiteLLM

Call 100+ LLMs using the OpenAI input/output format. Centralized spend tracking, load balancing, rate limiting, and circuit breakers.

Verified Real-World Production Workflow

Primary Implementation:

Prevent downtime by automatically failing over from Anthropic Claude to Gemini 2.5 Pro or DeepSeek if rate limits or 500 errors hit.

Engine Stack & Dependencies:

Python async proxy, Redis cache, OpenTelemetry instrumentation.

Target Persona & Role Fit

Backend & Cost Engineers

Engineered and benchmarked specifically for Backend & Cost Engineers demanding deterministic execution, low token overhead, and production reliability in agentic loops.

Production Blueprint & Installation

git clone https://github.com/BerriAI/litellm

Technical Specification (ASD-STE100)

Call 100+ LLMs using the OpenAI input/output format. Centralized spend tracking, load balancing, rate limiting, and circuit breakers.
Architecture: Python async proxy, Redis cache, OpenTelemetry instrumentation.

Domain Tags & Keywords

#proxy#failover#cost-tracking#multi-provider

Compute Efficiency Profile

P95 EXECUTION LATENCY
28ms
1.4x faster than median
TOKEN EFFICIENCY SAVINGS
-96%
Measured via context pruning
HEAD-TO-HEAD WIN RATE
72%
Arena paired matches
Monthly Documentation & Site Visits
920k/mo
Measured via Traffic Research bypass engine (1.1x category median)
Google Search Keyword Demand
88,000/mo
+68% YoY expansion

6-Month Web Traffic Velocity

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

LiteLLM Median
920k 675k 430k MayJunJulAugSepOct May · 430.1k vs 680.0k med This Skill: 430.1k -249.9k vs Median Jun · 528.1k vs 714.0k med This Skill: 528.1k -185.9k vs Median Jul · 626.1k vs 748.0k med This Skill: 626.1k -121.9k vs Median Aug · 724.0k vs 782.0k med This Skill: 724.0k -58.0k vs Median Sep · 822.0k vs 816.0k med This Skill: 822.0k +6.0k vs Median Oct · 920.0k vs 850.0k med This Skill: 920.0k +70.0k 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.

1192
±18 CI
1k 1k 1k MayJunJulAugSepOct May · 1.2k vs 1.2k med This Skill: 1.2k -25 vs Median Jun · 1.2k vs 1.2k med This Skill: 1.2k -19 vs Median Jul · 1.2k vs 1.2k med This Skill: 1.2k -5 vs Median Aug · 1.2k vs 1.2k med This Skill: 1.2k +6 vs Median Sep · 1.2k vs 1.2k med This Skill: 1.2k +5 vs Median Oct · 1.2k vs 1.2k med This Skill: 1.2k -6 vs Median
WIN RATE
72%
Head-to-head
WEEKLY SURGE
+227.5%
Adoption velocity
P95 LATENCY
28ms
Execution speed
TOKEN OVERHEAD
-96%
Context saved

Head-to-Head Comparison — LiteLLM 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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