ZeroGPU AI

If you're using a frontier AI like ChatGPT or Claude to perform basic adtech tasks like classification - save your $$$. We just dropped our specialized small language models for adtech. Thanks to @adexchanger for covering the launch in our first-ever feature interview.

Then cut down further on your inference costs by routing your repeatable workloads to task-specific SLMs. Save your frontier model tokens for the work that needs it. Customers are seeing 10x faster latency and 6x+ lower cost per request. zerogpu.ai/use-cases

Most teams are paying more for frontier models for simple tasks that don't need that level of complex reasoning. That’s why we’ve built a compute-efficient layer for AI inference. Tap into open-weight models through an OpenAI-compatible API or via our Claude Code Plug-in, with support for GLM-5.2, gpt-oss-120b, Qwen3, Llama 3.1, DeepSeek & Moonshot Kimi K2. Get started: zerogpu.ai

Cut your AI inference spend. Save frontier models for high-level reasoning. Use our SLMs for everything else. Check it out on ClawHub: clawhub.ai/zerogpu/plugin…

Three commands to install: npm install -g zerogpu-cli zerogpu login openclaw plugins install clawhub:zerogpu-router Docs → #openclaw" target="_blank" rel="nofollow noopener">docs.zerogpu.ai/integrations/o…

ZeroGPU Router plugin is now on OpenClaw 🎊 Your host model is doing a lot of work you shouldn't be paying frontier prices for. Now with our router, your host model only takes on your highest-level reasoning tasks. The repeatable work runs on our SLMs and nano models. 20+ skills available. Three commands to install

Kimi K3 (open weights, coming soon)

@JensenHuang @nvidia Open source FTW!

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. images.nvidia.com/pdf/Open-Weigh…

Huge credit to the @Kimi_Moonshot team for releasing the weights. Though we are focused on our edge network, open-source is a good thing!

$0.05 / 1M input tokens $0.30 / 1M output tokens Where it fits: → Agents and multi-step automation → Code assistance → Structured data tasks → Any high-volume production workload where speed and cost efficiency matter Get started: docs.zerogpu.ai/api-reference/…

Qwen3-30B is now live on ZeroGPU, and right now we are the most cost-effective way to run it in production. Move your production reasoning workloads to our edge network and pay a fraction of what closed frontier models charge. Docs to get started ⬇️

Stop paying closed-model prices for your production reasoning workloads. Start building today: 📖 Docs: docs.zerogpu.ai/models/gpt-oss… 🌐 Site: zerogpu.ai

The best part? Unbeatable pricing for early adopters: ⚡ $0.03 / 1M input tokens ⚡ $0.10 / 1M output tokens Offload complex reasoning tasks from closed frontier models to an open-weight powerhouse at a fraction of the cost.

We just added gpt-oss-120b to ZeroGPU 🚀 For early adopters looking to build with top-tier open reasoning models, ZeroGPU is now the least expensive way to run gpt-oss-120b in production. 🧵👇

@GoogleDeepMind Amazing. We still think SLMs are pretty good and much cheaper at some of these tasks. Feel free to try them out on our platform. Gemma coming soon!

We’re rolling out three new models to make AI agents faster, smarter, and cheaper at scale: 🔵 Gemini 3.6 Flash: It uses fewer tokens than 3.5 Flash to deliver higher quality work at the exact same cost. 🔵 Gemini 3.5 Flash-Lite: A fast, cost-effective option for everyday tasks like processing documents and agentic search. 🔵 Gemini 3.5 Flash Cyber: A cybersecurity model built to find and patch critical software vulnerabilities.

Check it out here clawhub.ai/zerogpu/plugin…

ZeroGPU Router is featured on the front page of ClawHub.com as a top plug-in! Cut your AI inference costs: route repeatable tasks and workflows to specialized SLMs that can run our edge-powered inference network. Try it today: zerogpu.ai

We are looking to get this up & running for you all on our edge device network soon!

@gsivulka It's a lot easier to experiment and figure out how to best deploy AI if you don't spend all of your budget in the R&D phase.

Right on the money. We started because we saw a need for companies to avoid the same perils as any other tech or management cycle. This is truly nothing new. We're trying to mitigate inefficient usage and bloat through deploying specialized and small language models through or edge network.