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Manifest

Free

Open-source LLM router for OpenClaw that optimizes model routing to save up to 70% costs.

Quick Facts

Pricing
Free
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Added
Mar 2026
Official URL
cdn.v2.qrcodekit.com

Tool overview

Overview

Manifest is an open-source LLM router designed to intelligently orchestrate requests across multiple large language models so you can ship AI

features

faster and cheaper. Built for modern AI stacks, Manifest optimizes which model is called for each request based on latency, pricing, quality constraints, and your own routing rules. This allows teams to offload routine workloads to more cost-effective models while reserving premium models for critical prompts—cutting infrastructure spend by up to 70% without sacrificing user experience. Manifest integrates seamlessly into existing applications through a clean API and flexible configuration. You can define routing strategies, fallback logic, and model selection criteria in code or configuration files, then monitor performance through structured logs and metrics. Because it is fully open source, you retain control over data, deployment, and customization, whether you run it on your own servers, within Kubernetes, or alongside OpenClaw-based systems. Ideal for AI-first products, internal tools, and experimentation environments, Manifest helps engineering teams avoid hard-coding model choices and vendor lock-in. Swap providers, introduce new open-source models, or run A/B tests on different LLMs with minimal changes to your codebase. With Manifest, you get an extensible routing layer that makes your LLM usage more reliable, observable, and cost-efficient—so you can focus on building better AI experiences rather than managing complex model fleets.

Screenshots

Manifest screenshot 1

Features

  • Dynamic multi-LLM routing
  • Cost-aware model selection
  • Latency and quality tuning
  • Configurable fallbacks and retries
  • Vendor-agnostic API interface
  • Open-source and self-hostable
  • Detailed logs and metrics
  • Easy integration with OpenClaw

Tags

Large Language Models (LLMs)
AI Developer Tools
Open Source AI Models
AI API

Use Cases

  • Optimize chat and assistant backends by routing simple prompts to cheaper models while reserving high-end LLMs for complex reasoning.

  • Power AI developer platforms that need a unified interface to multiple commercial and open-source LLM providers.

  • Run A/B tests across different language models to compare quality, latency, and cost before standardizing on a stack.

  • Build internal tools that must meet strict budget constraints while still supporting reliable AI-driven workflows.

  • Migrate between LLM vendors or add new models without refactoring application logic or breaking client integrations.

Frequently Asked Questions

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