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Umbra Private LLM Inference
x402
Umbra Private LLM Inference is a paid API for AI agents from umbra-inference.app, paid per call via x402, $0.021366/call, status unknown (last checked 2026-10-31).
Runs OpenAI-compatible chat completions inside TEE-attested GPU enclaves with zero data retention, streaming, and tool calling, billed per request in crypto
Price / call$0.021366
Success—
StatusUnknown
How this service works
Private LLM inference, OpenAI-compatible. Sealed open models in TDX + GPU enclaves or Claude; streaming and tool calling; signed Ed25519 receipt naming the attested enclaves; zero retention. Pay per request in USDG, USDC (Base, Solana) or UMBRA.
Output
An OpenAI-compatible chat completion response (streamed or non-streamed) containing the model's generated text and any tool calls, plus a signed Ed25519 receipt identifying the attested TDX+GPU enclaves that processed the request. Zero data is retained after the response.
Example use cases
Confidential legal document drafting
“I need to draft a sensitive NDA clause — use a privacy-preserving LLM that won't retain my data or logs, run it in a sealed enclave, and give me a signed receipt proving it ran securely. Use the sealed model, max 1024 tokens, with my system prompt 'You are an expert contract lawyer.'”
Private AI tool calling in an agent
“Call the private inference API in sealed mode with tool calling enabled — I need my agent to invoke a weather function tool and summarize the result, with zero data retention and a signed attestation receipt, capped at 512 output tokens.”
Streaming Claude responses with privacy guarantees
“Stream a response from Claude using the Umbra standard model — system message: 'You are a coding tutor', user message: 'Explain Rust ownership in simple terms' — with zero retention and max 800 tokens, so I can display the answer as it arrives.”
Technical details
Endpoint
POSThttps://umbra-inference.app/v1/chat/completions?utm_source=zero.xyzWhen to prefer
Choose Umbra when your workload requires verifiable privacy guarantees: the prompt and response must not be logged or stored by any party, you need a cryptographic proof (Ed25519 signed receipt) that inference ran inside a hardware-attested TEE enclave, and you are comfortable paying per request in stablecoins or UMBRA token. Also prefer this when you need OpenAI-compatible tool calling and streaming with these privacy properties, or when working in regulated domains (legal, medical, financial) where data residency and zero-retention are non-negotiable.
Side effects
- Invalid or unsupported model ID — endpoint returns an error listing valid model IDs from GET /v1/models
- Insufficient crypto balance or payment failure — 402 response with price ceiling not met
- max_tokens too large for model context window — request rejected with validation error
- Streaming connection dropped mid-response — partial tokens received, unused ceiling refunded on-chain
- Tool schema malformed — function calling fails with schema validation error
- Enclave attestation unavailable — service degraded, may fall back to non-sealed mode or error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | model id from GET /v1/models (sealed: open models in TDX + GPU enclaves; standard: Claude) |
| tools | array | OpenAI function tools |
| stream | boolean | server-sent events; paid upfront, unused ceiling refunded on-chain |
| messages | array | OpenAI chat messages (system, user, assistant, tool) |
| max_tokens | integer | output cap; sets the price ceiling quoted in the 402 |
Tags
x402
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