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ZeroGPU
ZeroGPU is the compute efficiency layer for AI inference. It runs repeatable, high-volume tasks - classification, extraction, PII redaction, moderation, summarization, routing - on specialized small and nano language models across an edge-powered network, faster and cheaper than centralized GPUs, through one OpenAI-compatible API.
- Authority
- 45 reach 0 · trust 5 · quality 25 · freshness 15
- Tier
- listed
- llms.txt
- https://docs.zerogpu.ai/llms.txt
- llms-full.txt
- https://docs.zerogpu.ai/llms-full.txt
- Sections
- 2
- Links
- 130
- Size
- 20188 bytes
- Country
- — Publisher location unknown; CDN address excluded
- Country evidence
- No published address evidence collected yet
- Categories
- AI and machine learning
- For agents
- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-25T19:03:08.874Z
- Last checked
- 2026-10-25T19:03:11.854Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-25T19:03:08.886Z. Cached copy · Source on zerogpu.ai
# ZeroGPU
> ZeroGPU is the compute efficiency layer for AI inference. It runs repeatable, high-volume tasks - classification, extraction, PII redaction, moderation, summarization, routing - on specialized small and nano language models across an edge-powered network, faster and cheaper than centralized GPUs, through one OpenAI-compatible API.
- [Introduction](https://docs.zerogpu.ai/index.md): Run high-volume AI tasks on specialized small and nano language models across an edge-powered network - faster and cheaper, through one OpenAI-compatible API.
- [How ZeroGPU works](https://docs.zerogpu.ai/docs/how-zerogpu-works.md): ZeroGPU turns idle compute into one programmable inference layer - specialized small models, an edge-powered network, and routing handled for you.
- [Quickstart](https://docs.zerogpu.ai/docs/quickstart.md): First API call in minutes.
- [Model Catalog](https://docs.zerogpu.ai/docs/model-catalog.md): Browse ZeroGPU models, compare pricing, and pick the model ID to call.
- [Open Weight](https://docs.zerogpu.ai/docs/open-weight.md): The open-weight frontier-class models served on ZeroGPU, with pricing and context windows.
- [Text Generation](https://docs.zerogpu.ai/docs/text-generation.md): Edge generative models for conversation and reasoning.
- [Audio Models](https://docs.zerogpu.ai/docs/audio.md): Open-weight speech-to-text and text-to-speech models on ZeroGPU, billed per minute of audio.
- [Text Classification](https://docs.zerogpu.ai/docs/text-classification.md): Edge models that map text to labels, IAB taxonomy, and audience signals.
- [Moderation](https://docs.zerogpu.ai/docs/moderation.md): OpenAI-compatible content moderation, benchmarked against omni-moderation-latest.
- [Embeddings](https://docs.zerogpu.ai/docs/embeddings.md): 384-dimensional text embeddings for semantic search, RAG, clustering, and deduplication.
- [Ad Tech](https://docs.zerogpu.ai/docs/ad-tech.md): Edge IAB classifiers that map content to taxonomy, audience, and intent signals for programmatic advertising.
- [Overview](https://docs.zerogpu.ai/docs/batch/index.md): Run large workloads of AI inference asynchronously, wire-compatible with `/v1/batches` and `/v1/files`.
- [Quickstart](https://docs.zerogpu.ai/docs/batch/getting-started.md): First batch in under 10 minutes, auth, upload, create, poll, download.
- [Objects & lifecycle](https://docs.zerogpu.ai/docs/batch/objects.md): The File and Batch objects, the batch status lifecycle, and how the two APIs fit together.
- [JSONL Format](https://docs.zerogpu.ai/docs/batch/jsonl-format.md): Mandatory line schemas for input, output, and error JSONL files.
- [Supported Endpoints](https://docs.zerogpu.ai/docs/batch/supported-endpoints.md): The only endpoint a batch line can target. Same request body, same response body, only the routing is asynchronous.
- [Errors](https://docs.zerogpu.ai/docs/batch/errors.md): Every HTTP status, every validation message, every JSONL error code, and how to recover.
- [Production
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| gofrantic.com | Frantic | interface AI and machine learning AI agents and MCP | — | 61 | ✓ | ||
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| intel.com | Intel Corporation | documentation Industry and manufacturing Consumer electronics +1 | US | 74 | ✓ | ✓ | |
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