OptiLLM

🚀 2-10x accuracy improvements on reasoning tasks with zero training

🤗 HuggingFace Space • 📓 Colab Demo • 💬 Discussions

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OptiLLM is an OpenAI API-compatible optimizing inference proxy that implements 20+ state-of-the-art techniques to dramatically improve LLM accuracy and performance on reasoning tasks - without requiring any model training or fine-tuning.

It is possible to beat the frontier models using these techniques across diverse tasks by doing additional compute at inference time. A good example of how to combine such techniques together is the CePO approach from Cerebras.

✨ Key Features

• 🎯 Instant Improvements: 2-10x better accuracy on math, coding, and logical reasoning
• 🔌 Drop-in Replacement: Works with any OpenAI-compatible API endpoint
• 🧠 20+ Optimization Techniques: From simple best-of-N to advanced MCTS and planning
• 📦 Zero Training Required: Just proxy your existing API calls through OptiLLM
• ⚡ Production Ready: Used in production by companies and researchers worldwide
• 🌍 Multi-Provider: Supports OpenAI, Anthropic, Google, Cerebras, and 100+ models via LiteLLM

🚀 Quick Start

Get powerful reasoning improvements in 3 simple steps:

# 1. Install OptiLLM
pip install optillm

# 2. Start the server
export OPENAI_API_KEY="your-key-here"
optillm

# 3. Use with any OpenAI client - just change the model name!

from openai import OpenAI

client = OpenAI(base_url="http://localhost:8000/v1")

# Add 'moa-' prefix for Mixture of Agents optimization
response = client.chat.completions.create(
    model="moa-gpt-4o-mini",  # This gives you GPT-4o performance from GPT-4o-mini!
    messages=[{"role": "user", "content": "Solve: If 2x + 3 = 7, what is x?"}]
)

Before OptiLLM: "x = 1" ❌
After OptiLLM: "Let me work through this step by step: 2x + 3 = 7, so 2x = 4, therefore x = 2" ✅

📊 Proven Results

OptiLLM delivers measurable improvements across diverse benchmarks:

Technique	Base Model	Improvement	Benchmark
MARS	Gemini 2.5 Flash Lite	+30.0 points	AIME 2025 (43.3→73.3)
CePO	Llama 3.3 70B	+18.6 points	Math-L5 (51.0→69.6)
AutoThink	DeepSeek-R1-1.5B	+9.34 points	GPQA-Diamond (21.72→31.06)
LongCePO	Llama 3.3 70B	+13.6 points	InfiniteBench (58.0→71.6)
MOA	GPT-4o-mini	Matches GPT-4	Arena-Hard-Auto
PlanSearch	GPT-4o-mini	+20% pass@5	LiveCodeBench

Full benchmark results below ⬇️

🏗️ Installation

Using pip

pip install optillm
optillm
2024-10-22 07:45:05,612 - INFO - Loaded plugin: privacy
2024-10-22 07:45:06,293 - INFO - Loaded plugin: memory
2024-10-22 07:45:06,293 - INFO - Starting server with approach: auto

Using docker

do