---
title: "OptiLLM Boosts Any AI Model's Reasoning by 30 Points Without Fine-Tuning"
subtitle: "An open-source proxy that stacks 20+ inference-time reasoning techniques onto any OpenAI-compatible endpoint, trading extra API calls for large accuracy gains."
url: "https://alphasignal.ai/news/optillm-boosts-any-ai-model-s-reasoning-by-30-points-without-fine-tuning"
author: "AlphaSignal Newsroom"
author_url: "https://alphasignal.ai/editorial-team"
company: "AlphaSignal"
company_url: "https://alphasignal.ai/company/alphasignal"
published: "2026-05-07T08:48:50.000Z"
updated: "2026-08-22T04:07:14.981Z"
type: "Repo"
topics:
  - "Infra"
  - "Reasoning"
subtopics:
  - "Inference Optimization"
  - "Model Serving"
  - "Test Time Compute"
upvotes: 104
source_url: "https://github.com/algorithmicsuperintelligence/optillm"
comments: 0
truncated: true
---

# OptiLLM Boosts Any AI Model's Reasoning by 30 Points Without Fine-Tuning

> An open-source proxy that stacks 20+ inference-time reasoning techniques onto any OpenAI-compatible endpoint, trading extra API calls for large accuracy gains.

Getting better reasoning out of an LLM usually means fine-tuning, swapping to a bigger model, or writing clever prompts. [OptiLLM](https://github.com/algorithmicsuperintelligence/optillm) takes a different route: it sits in front of your existing API as a drop-in OpenAI-compatible proxy and spends extra tokens at inference time to squeeze more accuracy out of whatever model you already use. The project has crossed 4,000 stars and ships more than 20 techniques you activate by prepending a slug to the model name.

Instead of one API call, the proxy issues several with different reasoning strategies, then combines or picks the best answer. You pay in latency and tokens, and get accuracy back.

## How the proxy actually works

You start the server, point your OpenAI client at `http://localhost:8000/v1`, and change the model string. Prefix `moa-` to activate Mixture of Agents, `mcts-` for Monte Carlo Tree Search, `plansearch-` for plan search, and so on. Everything else in your client code stays identical.

```
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8000/v1")
response = client.chat.completions.create(
    model="moa-gpt-4o-mini",
    messages=[{"role": "user", "content": "Solve: If 2x + 3 = 7, what is x?"}]
)
```

Two other invocation styles work: pass `optillm_approach` inside `extra_body`, or wrap the slug in `<optillm_approach>`

_Preview only. Full text requires an AlphaSignal Pro account._

## Sources

- [algorithmicsuperintelligence/optillm on GitHub](https://github.com/algorithmicsuperintelligence/optillm)
- [Mixture-of-Agents Enhances Large Language Model Capabilities](https://arxiv.org/abs/2406.04692)
- [CePO: Empowering Llama with Reasoning using Test-Time Compute](https://cerebras.ai/blog/cepo)
- [OptiLLM HuggingFace Space](https://huggingface.co/spaces/codelion/optillm)