The compute efficient layer for AI inference
Austin, TX
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Not every task needs a frontier model.
More than 40% of OpenRouter spend is already SLM-ready. By switching to the right small language model, you can reduce latency, cut costs by 5x.
We have more models coming soon. Stay tuned!
zerogpu.ai
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Our ZLM for IAB classification beat GPT-5.4 nano in 66% of 10,000 blind tests, about 10x faster, at about a tenth of the price.
Built for publishers, SSPs and web-data companies.
zerogpu.ai/benchmarks/iab-cl…
ALT ZeroGPU card for zlm-v1-iab-classify-edge. Reads a web page and says what it is about, so the right ads can run next to it. For publishers, ad platforms and web data teams. Benchmark figures: 66% win rate against gpt-5.4 nano, 48 ms p50 latency, against ~1,900 ms, 0 hallucinated labels, against 1,796.
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We'll be highlighting what you can do with our ZLMs: ZeroGPU Language Models.
Small models trained for one job each, like classifying, moderating and extracting from text. One job a day, with the industries it's built for.
docs.zerogpu.ai/docs/model-c…
ALT ZeroGPU card for ZLMs. Small AI models that each do one job well, instead of one big model doing everything. For any team running AI at scale. Benchmark figures: 5 zlms in the catalog today, 50+ languages, no translation step, $0.02 per 1m input tokens.
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Limelight enriched 2.88M prospect rows on ZeroGPU in six weeks.
9.2x cheaper than Claude Haiku, 3.2x cheaper than Gemini 3.5 Flash-Lite, $12,739 saved. Signup to production in 34 hours.
Case study: zerogpu.ai/case-study/limeli…
ALT Limelight case study card: 2.88 million prospect rows enriched on ZeroGPU in six weeks, 9.2x lower cost than Claude Haiku and 3.2x lower than Gemini 3.5 Flash-Lite, $12,739 saved.
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Save up to $10,000 in AI inference credit matching with committed usage on ZeroGPU.
Cut your AI spend by switching to our growing catalog of task-specific Small Language Models.
Using open-weight models like DeepSeek, GLM, Qwen, gpt-oss and Llama? ZeroGPU is the the most cost effective way to run that AI inference in production.
Get started -> zerogpu.ai
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Qualifying usage also comes with no rate limits.
Save your frontier models for your highest-level reasoning tasks. For everything else, use ZeroGPU.
Learn how we cut AI inference by more than 5x, by running SLMs on-edge at zerogpu.ai
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We already shared the first Small Language Model we've made open via @huggingface.
Now here's a deep dive on the SLMs we've released and why our approach is to make these models open.
Full story below 👇
Made with AI
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Over 40% of AI tasks can be moved to small language models today.
By switching to the right small language model, you can reduce latency and cut your AI spend by more than 5x.
The full blog:
medium.com/zerogpu/building-…
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You can now access our ZeroClick agent storefront on Locus Pro.
Agents can find our specialized small language models and pay from a Locus wallet to tap into cost-effective AI inference.
No signup, no API key. Just a better use of your AI spend.
All ZeroClick-powered Agent Storefronts are now listed as verified services on Locus Pro 🔥
If you want to sell your product to AI agents, set up an Agent Storefront with ZeroClick!
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Two new small language models are live on ZeroGPU: embeddings, to power semantic search RAG, clustering, and deduplication.
This is the model layer that lets your app match things by meaning instead of by keyword: A user types "cancel my plan." Your help center article says "end your subscription." An embedding model ensures the right recommendation is returned.
More than 40% of these kidns of enterprise AI tasks can run for less by switching to our SLMs.
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What teams build with this model:
→ Search that returns the right answer when the wording does not match
→ RAG, finding the correct documents before they go to a frontier model
→ Deduplication across records, listings, and support tickets
→ Recommendations and "more like this"
→ Clustering thousands of reviews or tickets by topic with no manual labeling
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Cut down on your AI inference costs!
Get started: docs.zerogpu.ai/docs/embeddi…
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ZeroGPU AI retweeted
We embraced @ZeroGPU_AI at @DappierAI early on.
Cut costs on 40% + of AI tasks by leveraging SLMs running at the edge.
As @GavinSBaker mentioned on a recent episode of @theallinpod the vast majority of tasks do not require frontier models; the recent report from OpenRouter underscores this.
ZeroGPU is building a new kind of inference cloud using Small Language Models - SLMs - orchestrated and running across a variety of edge devices, freeing up data centers for higher leverage tasks.
Every nook and cranny of compute will be taken up and is the greatest bottleneck to AI progress - creative solutions like ZeroGPU will help meaningfully unlock the market.
Give them a try!
Not every task needs a frontier model.
More than 40% of OpenRouter spend is already SLM-ready. By switching to the right small language model, you can reduce latency, cut costs by 5x.
We have more models coming soon. Stay tuned!
zerogpu.ai
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ZeroGPU AI retweeted
Not every token needs a frontier model.
40.5% of @OpenRouter spend is SLM-ready.
@ZeroGPU_AI has models that can cover all these flows with SLMs
- workflow execution: 19%
- classification: 9.8%
- extraction + transformation: 8.3%
- summarization + tool dispatch + memory: 3.4%
Right model. Right task.
We have more models coming soon. Stay tuned!
lnk.bio/zerogpu
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ZeroGPU is now an @nvidia Inception member!
This gives us deeper access to the NVIDIA platform, tooling and ecosystem as we work to cut the cost of AI inference.
Run high volume workloads on our small and open-weight models on-edge.
- 5x savings
- 10x reductions
- the same accuracy at a fraction of compute
If you’re ready to start cutting your AI spend, check out our SLM catalog.
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Frontier models are great for high-level reasoning, but you don’t always need those expensive models.
We pair the most common AI tasks with idle compute.
Get started today.
zerogpu.ai
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The future of AI should be built in the open.
ZeroGPU already makes leading open-weight models easier and more affordable to run. Now, we're taking the next step: making our own task-specific models openly available for developers to download, adapt, and deploy.
Starting with zlm-v1-signal-extract, which extracts keywords and user intent in a single pass. The model weights are now available on Hugging Face under the Apache 2.0 license. 🤗
It beats GPT-5-nano on both tasks its built for, while running ~9× faster.
huggingface.co/ZeroGPU/zlm-v…
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Its part of a broader commitment to make more of our specialized models openly available as our catalog grows.
Part of that is giving developers the freedom to run them through ZeroGPU or deploy them wherever they choose.
Want to run a hosted version of this model? platform.zerogpu.ai
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ZeroGPU is heading to Chicago tomorrow for @1871tech's Emerging Tech Innovation Summit: Scale the System.
The lineup is stacked - Anthropic, Microsoft, Waymo, Stanford HAI & more.
We’ll be there to talk about how we're cutting AI inference costs, by moving tasks to specialized SLMs that run on-edge.
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