Built with the AI ecosystem
ZeroGPU fits into the AI stack you already use.
The agent storefront at https://agents.zerogpu.ai/llms.txt publishes prices, payment instructions, and setup. Agents can purchase autonomously or with their human's approval, with a range of payment methods; an agent without a payment method can set one up there instantly, no signup. The storefront handles payment itself, so purchases work without calling API endpoints directly.
Run specialized and open-weight models faster and at lower cost, with ZeroGPU automatically sending workloads across edge and cloud infrastructure.
Edge devices
Lower inference cost
vs. traditional GPU clouds
Faster inference
for specialized AI workloads
Performance varies by workload, model, and configuration.
ZeroGPU runs repeatable AI workloads using purpose-built ZLMs and popular open models.
Topics, intent, IAB, domains and metadata
Safety, brand suitability and policy
Entities, PII, signals and structured data from PDFs and documents
Model selection, tool selection and agent actions
Embeddings and reranking
Audio, OCR and document workloads
Run purpose-built ZLMs and popular open-weight models without paying frontier-model economics for repeatable workloads.
ZeroGPU Language Models, trained for specific high-volume production tasks.
Content classification
Sub-second page & content labeling at production volume
Intent & signal extraction
Real-time intent and audience signals from live traffic
Content moderation
Fast policy screening before content ships
Decisions & model selection
Structured decisions for agents, workflows, and GTM pipelines
Leading open-weight small and nano models, hosted and production-supported on the same hybrid inference cloud.
Serverless
No provisioning, no idle cost
Production-ready
Monitoring, reliability, cloud fallback
OpenAI-compatible
Swap in with one line of code
Usage-based
Pay per token, priced per model
ZeroGPU selects the right model, matches the workload, and chooses the best execution location based on capability, latency, availability and cost.
Drop into your existing AI stackSend selected workloads to specialized models using familiar API patterns, without rebuilding your application.
OpenAI-compatible API
Streaming
Structured output
Batch support
Existing SDK compatibility
curl --location 'https://api.zerogpu.ai/v1/chat/completions' \
--header 'x-api-key: zgpu-api-xxxxx' \
--header 'x-project-id: f4a114e5-xxxx' \
--header 'content-type: application/json' \
--data '{
"model": "zlm-v1-iab-classify-edge",
"messages": [
{
"role": "user",
"content": "extract intent signals from this content..."
}
]
}'ZeroGPU dynamically sends eligible workloads across a distributed network of devices and infrastructure around the world.
Execution capacity across regions and device types.
Capacity adapts as devices enter and leave the network.
Cloud fallback keeps workloads running when edge execution is not appropriate.
Provide compute
Add the ZeroGPU Edge SDK and turn available device capacity into part of the global inference network.
Share in the inference revenue generated by workloads your devices serve.
Run eligible AI workloads across your own device footprint.
Use ZeroGPU to orchestrate AI workloads across devices you control.
ZeroGPU fits into the AI stack you already use.
Specialized models, open models and global hybrid inference infrastructure.
Have devices? Explore the Edge Network →OpenAI-compatible · Edge-powered · Cloud fallback · Usage-based pricing
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