Vast.ai vs Inference — Comparison

Vast.ai

Real-Time GPU Pricing

Vast.ai is a GPU compute marketplace founded on one idea: whoever controls compute controls AI. We exist to make sure that power stays distributed. Christian Horne — a fellow thinker and builder who also published on LessWrong — shared Jake's view that the compute scaling thesis had profound implications, not just for AI development, but for who would control it. Both saw the same thing: if whoever controlled the most compute controlled the most powerful AI, then the future of artificial general intelligence would be determined by who had the deepest pockets, not who had the best ideas. On June 28, 2016, they incorporated Vast.ai. The founding thesis fit on a napkin: the world was full of underutilized GPU hardware — in gaming rigs, mining farms, research labs, and small data centers — and the people who needed that compute most couldn't afford the hyperscaler rates. But the motivation was never purely commercial. A world where compute flows freely to thousands of independent researchers is a fundamentally different world than one where it is locked behind the pricing walls of a few incumbents. “A world where compute flows freely to thousands of independent researchers is a fundamentally different world than one where it is locked behind the pricing walls of AWS, GCP, and Azure.” What Jake predicted. What the team built. How the field caught up. Jake Cannell publishes a series of essays on LessWrong arguing that intelligence is fundamentally a function of compute — not clever algorithms or hand-engineered modules. Christian Horne (lahwran), a fellow LessWrong contributor, shares the same conviction. The two become collaborators. AlexNet breaks ImageNet benchmarks by scaling a known neural network architecture on GPUs — exactly as the scaling hypothesis predicted. The deep learning revolution begins. Jake publishes his landmark essay arguing that the human brain is a single, general-purpose learning algorithm — not a zoo of specialized circuits. He predicts AlphaGo two years before it happens and forecasts human-level vision (~2024±3) and language via scaled deep learning. Jake Cannell and Christian Horne incorporate Vast.ai as a Delaware C Corporation. The founding thesis: the world is full of underutilized GPU hardware, and the people who need that compute most can’t afford hyperscaler rates. The market needs a two-sided platform. For two years, Jake and Christian build the marketplace platform end-to-end: host onboarding, search interface, pricing engine, Docker-based instance management — engineered to work across heterogeneous hardware and wildly different network conditions. Vast.ai launches — not with a press release, but the way honest products launch: to friends, family, and a post on Hacker News. GPU compute 3–5x cheaper than AWS, available in seconds, no enterprise contract required. Early independent hosts join the platform. The marketplace concept is validated — developers get cheaper GPUs, hosts monetize idle har

Inference

Train, deploy, observe, and evaluate LLMs from a single platform. Lower cost, faster latency, and dedicated support from Inference.net.

Based on the social mentions, users are primarily concerned with **cost optimization and performance efficiency** for AI inference. There's significant discussion around pricing strategies, with founders seeking guidance on appropriate markup multipliers (3x-10x) from token costs to customer pricing. The community shows strong interest in **cost-saving alternatives** like open-source solutions and performance optimizations, with mentions of tools that reduce inference expenses and improve speed (like IndexCache delivering 1.82x faster inference). Users appear frustrated with **expensive closed APIs** and are actively seeking more affordable, deployable alternatives that don't compromise on quality, as evidenced by interest in open-weight models and specialized inference hardware.

Vast.ai

Inference

Vast.ai

Inference

Vast.ai

Inference