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optillm

OpenAI-compatible proxy applying inference-time reasoning techniques

Stars
4.3k
License
Apache-2.0
Last commit
Oct 2026
Last release
Sep 2026

Overview

OptiLLM is an OpenAI-compatible proxy (pip or Docker, port 8000) that applies inference-time techniques such as mixture of agents, N-sample selection, self-consistency, MCTS, CePO and MARS to any upstream model, selected by a model-name prefix like moa-gpt-4o-mini. Plugins add an MCP client, memory, PII anonymization, code execution, JSON outputs and provider failover; upstreams are OpenAI, Cerebras, Azure or anything LiteLLM supports.

Who it is for: developers squeezing more reasoning accuracy from existing models

Strengths

  • 20+ techniques selected by model-name prefix, e.g. moa-gpt-4o-mini
  • Per-technique benchmarks listed (MARS +30 points on AIME 2025 with Gemini 2.5 Flash Lite)
  • Plugins for MCP client, memory, PII anonymization, code execution, JSON output
  • Works with any OpenAI-compatible endpoint; LiteLLM covers other providers

Weaknesses

  • Techniques multiply upstream calls (bon, MoA, MCTS), raising cost and latency
  • Runs on Flask's development server by default
  • Decoding techniques (cot_decoding, AutoThink) need the local inference path
  • Web search plugin drives Chrome through Selenium

What it needs

  • GPU optional
  • Docker + Compose
  • Models: OpenAI, Cerebras, Azure OpenAI, any OpenAI-compatible endpoint, LiteLLM providers, local models via the built-in inference server
  • port 8000

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