Harness Hub
All startups

Magnitude

An open-source inference engine for agents that tunes its kernels to your hardware.

Magnitude is an open-source local inference engine that tunes its kernels on the user's hardware to find the fastest way to run each open model, which it says is over 2x faster than Ollama (company claim). It launched on Hacker News in September 2026 with 194 points. Y Combinator S25.

In the news

Hey HN, Anders and Tom here. We're building Magnitude, an inference engine for agents that optimizes itself to run as fast as possible on your hardware. It works on Mac, Linux, and Windows on any hardware and is up to 2x faster than llama.cpp. We're both software engineers and...

Serverless cloud built for AI and agentic compute.

Modal lets teams run inference, fine-tuning and arbitrary agent workloads as serverless Python without managing infrastructure — a common substrate for harness backends at scale.

4 pros · 4 cons

Durable execution for long-running agent workflows.

Temporal's durable execution engine is widely adopted to make agent pipelines reliable: state survives crashes, retries are automatic, and workflows run for minutes or months. A key piece of serious harness infrastructure.

$430M total · $300M Series D (Feb 2026) at $5B valuation

3 pros · 4 cons

Durable functions and workflows for AI agents.

Inngest runs agent logic as durable steps — queueing, retries, concurrency control and human-in-the-loop waits — without operating your own workflow infrastructure.

4 pros · 5 cons

Sources

  1. Magnitude homepage
  2. Magnitude repository