Referință API Hypereal
O cheie API ck_ cu prefixul -. REST compatibil cu OpenAI. Integrați-l în Claude Code, Codex CLI, Cursor, OpenAI SDK, Anthropic SDK sau apelați-l direct cu curl. Chat, imagini, video, audio, agenți de cod — toate în spatele unui singur URL de bază.
01 · Începeți în 90 s
Pornire rapidă
Creați o cheie, setați clientul la hypereal.cloud, și lansați. Autentificarea și structura cererilor sunt compatibile cu OpenAI — majoritatea SDK-urilor funcționează schimbând doar base URL-ul.
Reîncărcați cel puțin $2 (200 credite) și creați o cheie la /manage-api-keys. Cheile încep cu ck_.
Base URL: https://hypereal.cloud/api/v1
Header-ul de autentificare este Authorization: Bearer ck_.... Aceleași corpuri de cerere OpenAI pe care le cunoașteți deja.
curl https://hypereal.cloud/api/v1/chat/completions \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.5",
"messages": [{"role": "user", "content": "Say hi in one word."}]
}'import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.HYPEREAL_API_KEY, // ck_...
baseURL: 'https://hypereal.cloud/api/v1',
});
const completion = await client.chat.completions.create({
model: 'gpt-5.5',
messages: [{ role: 'user', content: 'Say hi in one word.' }],
});
console.log(completion.choices[0].message.content);For coding agents, start withclaude-sonnet-4-6and use Claude Code or another Anthropic-compatible client that sendscache_control. Hypereal supportscache_controlcaching and Hypereal Cache. Hypereal Cache is on by default and can sharply reduce token consumption for repeated coding-agent context. You can sethypereal.cacheto"auto"explicitly, or omit it for the same default.
SDK
Hypereal SDK
Install hypereal-sdk for typed access to chat, responses, image generation, video generation, audio, jobs and storage from Node.js 18+.
Published as hypereal-sdk on npm.
Use client.images.generate(), chat, responses, jobs and storage.
See the full SDK overview at /sdk.
pnpm add hypereal-sdk
import { Hypereal } from 'hypereal-sdk';
const client = new Hypereal({
apiKey: process.env.HYPEREAL_API_KEY!,
});
const image = await client.images.generate({
model: 'gemini-3-1-flash-t2i',
prompt: 'A cinematic portrait in neon light',
aspect_ratio: '16:9',
});
console.log(image);const object = await client.storage.uploadFile(file, {
filename: 'training-image.png',
contentType: 'image/png',
kind: 'dataset',
});
const listed = await client.storage.list({ kind: 'dataset' });02
Autentificare
Fiecare cerere necesită o cheie cu prefixul ck_. Trei forme de header acceptate acoperă toate SDK-urile.
Bearer ck_... — folosit de OpenAI SDK, Codex CLI și Cursor.ck_... — folosit de Anthropic SDK și Claude Code pe /v1/messages.ck_... — forma nativă Google Gemini SDK /, acceptată de /v1/gemini.?key=ck_... funcționează și.03 · Compatibil cu OpenAI
Chat Completions
Endpoint-ul de bază. Formatul wire OpenAI Chat Completions. Folosit pentru GPT, Gemini, Qwen, DeepSeek, GLM și orice alt LLM non-Anthropic.
/api/v1/chat/completionsCorpul cererii
/v1/messages în schimb.role, content).false. Flux SSE când true; utilizarea este inclusă în ultimul chunk.Prețuri
Facturat per token, folosind rata de input/output a fiecărui model. 100 credite = $1.00. Soldul minim pentru a apela endpoint-ul este de 200 credite ($2.00).
curl https://hypereal.cloud/api/v1/chat/completions \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.5",
"messages": [
{"role": "system", "content": "You are a terse assistant."},
{"role": "user", "content": "Two-line haiku about caches."}
],
"stream": true,
"max_tokens": 256
}'import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.HYPEREAL_API_KEY,
baseURL: 'https://hypereal.cloud/api/v1',
});
const stream = await client.chat.completions.create({
model: 'gpt-5.5',
stream: true,
messages: [{ role: 'user', content: 'Stream me a haiku.' }],
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? '');
}Modele compatibile cu OpenAI și providerii
gpt-5gpt-5.1gpt-5.2gpt-5.3gpt-5.4gpt-5.5gpt-5.5-instantgpt-5.5-progpt-5.4-minigpt-5.4-nanogpt-5.4-officialgpt-5.4-pro-officialgpt-5.2-officialgpt-5-pro-officialgpt-realtime-1.5-officialgpt-audio-1.5-officialglm-5qwen3.5-plusqwen3.5-flashqwen3-maxdeepseek-v3.2kimi-k2.5MiniMax-M2.5nano-banana-204 · Compatibil cu Anthropic
Messages
Formatul wire Anthropic /v1/messages cu extended thinking, failover multi-upstream și keepalive SSE de 15 secunde. Folosiți-l pentru Claude Code, OpenCode, OpenClaw și SDK-ul oficial Anthropic.
/api/v1/messagesCorpul cererii
claude-sonnet-4-6, claude-opus-4-6, sau claude-haiku-4-5. ID-urile Anthropic mai vechi (claude-sonnet-4-5-20250929, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022) sunt aliasate automat la cele mai recente echivalente.system,tools, or text content blocks for Anthropic prompt caching. Hypereal defaults a cache breakpoint when omitted and reports cache usage in response metadata."auto" to make the default explicit for repeated requests, orfalse to bypass it for a request.budget_tokens limitează traseul de raționare. Endpoint-ul trimite ping-uri SSE la 15 s pentru a împiedica proxy-urile să închidă stream-urile lungi de thinking.curl https://api.hypereal.cloud/v1/messages \
-H "x-api-key: ck_..." \
-H "anthropic-version: 2023-06-01" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-sonnet-4-6",
"max_tokens": 1024,
"system": [{
"type": "text",
"text": "You are a senior TypeScript refactoring assistant.",
"cache_control": {"type": "ephemeral"}
}],
"messages": [
{"role": "user", "content": "Plan a 3-step refactor of a Next.js app."}
],
"hypereal": {"cache": "auto"}
}'import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic({
apiKey: process.env.HYPEREAL_API_KEY, // ck_...
baseURL: 'https://api.hypereal.cloud',
});
const msg = await client.messages.create({
model: 'claude-sonnet-4-6',
max_tokens: 1024,
system: [{
type: 'text',
text: 'You are a senior TypeScript refactoring assistant.',
cache_control: { type: 'ephemeral' },
}],
hypereal: { cache: 'auto' },
messages: [{ role: 'user', content: 'Hello, Claude.' }],
});
console.log(msg.content);Modele Anthropic
claude-opus-4-6claude-sonnet-4-6claude-haiku-4-505 · OpenAI Responses API
Responses
Noul OpenAI Responses API (folosit de modul `wire_api = responses` din Codex CLI și de OpenAI Agents SDK). Aceeași autentificare ca pentru chat/completions; corpul cererii folosește `input` în loc de `messages`.
/api/v1/responsesNote
- Modelele Anthropic returnează un 400 — ele aparțin la
/v1/messages. - Streaming-ul și non-streaming-ul sunt facturate ambele pe baza
response.usage.input_tokens/output_tokens. - Unele upstream-uri emit întotdeauna SSE — endpoint-ul detectează asta și face stream transparent chiar dacă
stream:false. - Failover multi-upstream. Setați un timeout mare la client (300s+).
curl https://hypereal.cloud/api/v1/responses \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.1-codex",
"input": "Write a TypeScript function that debounces a callback.",
"stream": true
}'import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.HYPEREAL_API_KEY,
baseURL: 'https://hypereal.cloud/api/v1',
});
const response = await client.responses.create({
model: 'gpt-5.3-codex',
input: 'Refactor this file into smaller modules.',
});
console.log(response.output_text);Modele optimizate pentru Codex
gpt-5-codexgpt-5-codex-minigpt-5.1-codexgpt-5.1-codex-minigpt-5.1-codex-maxgpt-5.2-codexgpt-5.3-codexgpt-5.3-codex-sparkgpt-5.3-codex-official06 · Codex CLI / Codex Desktop
Codex CLI
Codex indică providerul `wire_api = responses` către /api/v1/responses. CLI-ul adaugă `/responses` la base URL, așa că configurați base URL-ul conform exemplului.
/api/v1/responses# ~/.codex/config.toml model_provider = "hypereal" model = "gpt-5.3-codex" [model_providers.hypereal] name = "Hypereal" base_url = "https://hypereal.cloud/api/v1" wire_api = "responses" env_key = "HYPEREAL_API_KEY"
Apoi exportați cheia:export HYPEREAL_API_KEY=ck_...
Rulați codex ca de obicei. Orice trimite Codex — fluxuri complete de raționare, apeluri de tool-uri, editări de fișiere — este transmis prin proxy neschimbat. Facturarea se bazează pe blocul standard de utilizare input_tokens / output_tokens .
Aceeași configurare funcționează pentru OpenCode, Claude Code (folosiți /v1/messages), Cursor (folosiți /v1/chat/completions), și Gemini CLI (folosiți /v1/gemini).
07
Generare de imagini
Format compatibil cu OpenAI /images/generations. Sincron — endpoint-ul returnează URL-uri de imagine (sau base64) când upstream-ul finalizează. Facturat per imagine; `n` este limitat la 1–10.
/api/v1/images/generationsCorpul cererii
image, reference_images).1024x1024, 1536x1024. În funcție de provider.creditsPerGeneration × n, endpoint-ul returnează 402.curl https://hypereal.cloud/api/v1/images/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "nano_banana_pro",
"prompt": "isometric studio shot of a tiny cyberpunk apartment, neon rim light",
"n": 1,
"size": "1024x1024"
}'const res = await fetch('https://hypereal.cloud/api/v1/images/generations', {
method: 'POST',
headers: {
'Authorization': `Bearer ${process.env.HYPEREAL_API_KEY}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'gemini-3-pro-image-preview',
prompt: 'a chrome teapot floating over the ocean at sunset',
n: 1,
}),
});
const { data } = await res.json();
console.log(data[0].url); // or data[0].b64_json depending on the modelGPT Image 2 — text-to-image & image-to-image
Use the same /api/v1/images/generations endpoint with "model": "gpt-image-2". Pass an array of public image URLs in reference_images to switch from pure text-to-image to image-conditioned generation (edits, restyles, character consistency).
sizeaccepts1024x1024,1536x1024(landscape),1024x1536(portrait),2048x2048,4096x4096. 2K and 4K are square only.- Reference images must be public HTTPS URLs (base64 is not accepted by this model). Up to 4 references per request.
- Pricing is per-tier: 1K, 2K, and 4K each have their own credit cost — see the model table below.
- Synchronous response: the call returns the final image URL (no polling needed). Allow up to ~120 s.
# Text-to-image (1K landscape)
curl https://hypereal.cloud/api/v1/images/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2",
"prompt": "a chrome teapot floating over the ocean at sunset",
"size": "1536x1024"
}'
# Image-to-image / edit
curl https://hypereal.cloud/api/v1/images/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2",
"prompt": "same character, snowy mountain background, golden hour",
"size": "1024x1024",
"reference_images": [
"https://example.com/source.jpg"
]
}'NanoBanana 2 — image-to-image & multimodal inputs
Model id gemini-3-1-flash-t2i (NanoBanana 2). Pass references in image_urls to switch into image-to-image / multi-reference mode. Up to 4 reference images, blended in prompt order. Use the standard aspect_ratio field — landscape, portrait, and square are all supported at every resolution tier.
- Supported
aspect_ratio: 1:1, 3:2, 2:3, 4:3, 3:4, 16:9, 9:16, 21:9. - Supported
resolution: 0.5K, 1K, 2K, 4K. - Reference images may be public HTTPS URLs or base64 data URLs.
- Multi-reference works with a text prompt — combine, e.g., a character + outfit + scene reference and describe the final composition in the prompt.
# Multimodal: text + multiple reference images
curl https://hypereal.cloud/api/v1/images/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3-1-flash-t2i",
"prompt": "Place the character (img 1) wearing the jacket (img 2) into the scene from img 3, cinematic light",
"aspect_ratio": "16:9",
"resolution": "2K",
"image_urls": [
"https://example.com/character.png",
"https://example.com/jacket.png",
"https://example.com/scene.png"
]
}'Modele de imagini
gpt-image-2gpt-4o-imagenano_banananano_banana_2gemini-3.1-flash-image-previewgemini-2.5-flash-image-previewflux-kontext-proflux-2-prodoubao-seedream-4-0doubao-seedream-4-5doubao-seedream-5-0gemini-3.1-flash-image-preview-officialflux-kontext-maxgemini-2.5-flash-image-officialnano_banana_progemini-3-pro-image-previewflux-2-flexgemini-3-pro-image-preview-officialgemini-3-pro-image-preview-4Kgemini-3.1-fast-imagengemini-3.1-thinking-imagen08 · long-running
Generare video
Endpoint video asincron — creați un job, apoi interogați periodic URL-ul jobului returnat până când clipul este gata. Facturarea se face per secundă pentru multe modele sau per clip pentru modele precum Gemini Omni Flash, Veo, Vidu și Grok.
/api/v1/videos/generateCorpul cererii
per_second .16:9, 9:16, 1:1. În funcție de provider.Gemini Omni Flash accepts 16:9 or 9:16.720P.last_image_url sau image — vedeți documentația upstream pentru acel model.curl https://hypereal.cloud/api/v1/videos/generate \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gemini_omni_flash",
"prompt": "a white cube rotating on a black background, clean product demo",
"duration": 6,
"aspect_ratio": "16:9",
"resolution": "720P",
"image_urls": [
"https://example.com/product-reference.png"
]
}'const res = await fetch('https://hypereal.cloud/api/v1/videos/generate', {
method: 'POST',
headers: {
'Authorization': `Bearer ${process.env.HYPEREAL_API_KEY}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'gemini_omni_flash',
prompt: 'a cat walking on the moon, cinematic, no text',
duration: 6,
aspect_ratio: '16:9',
resolution: '720P',
image_urls: ['https://example.com/cat-reference.png'],
}),
});
const data = await res.json();
console.log(data.jobId, data.pollUrl); // poll /v1/jobs/{id} for the mp4Modele video
gemini_omni_flashwan2.6-flashkling-2-6MiniMax-Hailuo-02doubao-seedance-1-0-pro-fastMiniMax-Hailuo-2.3wan2.6kling-video-o1kling-v3-omnikling-v3kling-v3-videodoubao-seedance-1-0-pro-qualitydoubao-seedance-2-0doubao-seedance-2-0-fastdoubao-seedance-1-5-proVeo3.1-fast-officialVeo3.1-quality-officialveo3.1-fastveo3.1-qualityvidu-q3-progrok-video-309 · Fish Audio
Audio — TTS, clonare vocală, ASR
Trei ID-uri de model folosesc același endpoint. Structura body-ului și a răspunsului depinde de modelul apelat. Providerul este Fish Audio (apelat direct, nu prin ToAPI), facturat per cerere.
/api/v1/audio/generationsaudio-tts și audio-clone.audio-asr (input) și audio-clone (voce de referință ≥ 10s).data: [{ url }] pentru TTS / clone, text (+ opțional segments, duration) pentru ASR.curl https://hypereal.cloud/api/v1/audio/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "audio-tts",
"text": "Welcome to Hypereal. One key, every model.",
"voice_id": "en_male_calm"
}'curl https://hypereal.cloud/api/v1/audio/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "audio-clone",
"text": "This is my cloned voice.",
"audio": "https://example.com/reference-30s.mp3"
}'curl https://hypereal.cloud/api/v1/audio/generations \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "audio-asr",
"audio": "https://example.com/recording.mp3"
}'Modele audio
audio-ttsaudio-cloneaudio-asr10 · Google native shape
Gemini
Acceptă atât formatul nativ Gemini (`contents` / `generationConfig` / `systemInstruction`), cât și formatul OpenAI pe același endpoint. Endpoint-ul convertește intern în OpenAI înainte de a transmite mai departe. Pentru majoritatea codurilor, /v1/chat/completions cu un ID de model Gemini este mai simplu.
/api/v1/geminitemperature, maxOutputTokens, etc.contents.Antet de autentificare: x-goog-api-key: ck_..., ?key=ck_..., sau Authorization: Bearer ck_... funcționează toate.
curl "https://hypereal.cloud/api/v1/gemini" \
-H "x-goog-api-key: ck_..." \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.5-thinking",
"contents": [
{"role": "user", "parts": [{"text": "Outline a launch plan."}]}
],
"generationConfig": {"temperature": 0.6, "maxOutputTokens": 2048}
}'// The /v1/gemini endpoint accepts both Gemini-native and OpenAI shapes.
// For SDK use, the OpenAI client + /v1/chat/completions is simpler.
const res = await fetch('https://hypereal.cloud/api/v1/gemini', {
method: 'POST',
headers: {
'x-goog-api-key': process.env.HYPEREAL_API_KEY!,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'gemini-3.5-fast',
contents: [{ role: 'user', parts: [{ text: 'Hi' }] }],
}),
});
console.log(await res.json());Modele Gemini
gemini-3-pro-officialgemini-3-pro-preview-officialgemini-3-flash-officialgemini-3-flash-preview-officialgemini-3.1-progemini-3.1-pro-preview-officialgemini-3.1-fastgemini-3.1-thinkinggemini-3.5-thinkinggemini-3.5-fastgemini-3.1-flash-lite-preview-officialgemini-2.5-pro-officialgemini-2.5-flash-officialgemini-2.5-flash-lite-officialgemini-2.0-flash-officialgemini-2.0-flash-lite-officialgemini-2.0-flash-vipgemini-2.5-flash-vipgemini-2.5-pro-vipgemini-3-flash-preview-vip11
Erori și limite de rată
Toate erorile sunt JSON de forma '{ error: { type, message } }'. Limitele de rată sunt evaluate per utilizator, nu per cheie — mai multe chei partajează aceeași cotă.
ck_ prefix), expirată sau inactivă.X-RateLimit-Limit, X-RateLimit-Remaining, și X-RateLimit-Reset sunt returnate în răspunsurile de limită de rată.model, ID de model necunoscut (răspunsul include available_models), sau endpoint greșit pentru format (de ex. un model Anthropic pe /chat/completions).DEVELOPER
ComfyUI as API
Deploy a ComfyUI container as a Hypereal-managed GPU endpoint. Same per-second billing, auto-scaling, webhook delivery as any other deployment — you control the workflow graph and the model weights.
/comfy workflow-JSON paster and /v1/comfy/* routes were retired. ComfyUI now ships as a regular Deployment — you bring a Docker image (e.g. runpod/worker-comfyui or your own), we mount it on real GPUs./v1/gpu/run/{slug}Submits a job to your ComfyUI deployment. Async by default; pass "sync": true to wait inline up to 240s.
curl -X POST https://hypereal.cloud/v1/gpu/run/my-comfy-workflow \
-H "Authorization: Bearer $HYPEREAL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": {
"prompt": "a cinematic portrait of an astronaut",
"seed": 42,
"workflow_overrides": { "Sampler.steps": 30 }
}
}'{
"job_id": "K3uA7Pq9xLm4",
"status": "queued",
"provider_job_id": "..."
}/v1/gpu/jobs/{id}Poll for status. We live-poll the worker on each request so you see queued → running → succeeded in near real time. On succeeded credits settle to the actual GPU-seconds; on failed we refund the hold. Pin a webhookUrl on the deployment to skip polling.
{
"job_id": "K3uA7Pq9xLm4",
"status": "succeeded",
"output": { "images": ["data:image/png;base64,..."] },
"executionMs": 18420,
"creditsCharged": 56
}# List
curl https://hypereal.cloud/v1/deployments \
-H "Authorization: Bearer $HYPEREAL_API_KEY"
# Create (point at any ComfyUI worker image)
curl -X POST https://hypereal.cloud/v1/deployments \
-H "Authorization: Bearer $HYPEREAL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"slug": "my-comfy-workflow",
"name": "My Comfy",
"dockerImage": "runpod/worker-comfyui:dev-cuda12.1.1",
"gpuTypes": "ADA_48_PRO,AMPERE_80"
}'Open /infra/deployments/new: pick a GPU tier, point at your ComfyUI Docker image (custom builds with your weights and custom nodes pre-baked work fine), set min/max workers and idle timeout. Your endpoint goes live in 60s.
Full Infrastructure docs: /docs/infra — handler spec, pricing, webhook protocol, R2 storage for weights.
ENTERPRISE
Gateway features
Cost visibility, budget guardrails, request logs, multi-provider failover, and smart routing — all built into the same API key. No extra setup, no separate dashboard tier.
Spend, by model, in real time
Per-model pie, daily cost trend, top-10 most expensive requests. Available on every account at /usage. Export the underlying logs to CSV at any time:
GET /api/api-usage/export?days=30 Authorization: session cookie → hypereal-usage-2026-05-10.csv
Per-key monthly cap, with email guardrails
Set spendingLimit on any API key. We email at 80% (heads up) and 100% (hard cap). Optional: auto-disable the key on overshoot so a runaway loop never costs you a four-figure invoice.
POST /api/api-keys
{
"name": "prod-eu",
"spendingLimit": 50000 // 500 USD / month
}Every call, searchable
Every API call is indexed by endpoint, model, status code, latency, and cost. Filter and search at /usage, or pull the JSON directly:
GET /api/api-usage?days=30&limit=1000
{
logs: [...],
costByModel: [...],
topExpensiveRequests: [...]
}Outages don't reach your users
Every supported model has a fallback chain. On 5xx, timeout, or 429 we transparently retry the next provider with exponential backoff. You always get a result or a single, clean error — never a flap.
primary: seedance-2-0-turbo-t2v (region us-east) fallback: seedance-2-0-t2v (region us-west) fallback: seedance-2-0 (region eu-central) retries: 1 per target, exp backoff
Pick by intent, we pick the cheapest qualified model
Send intent instead of model and we'll route to the cheapest provider in that capability bucket — without giving up determinism: pin a model whenever you want and we'll honor it exactly.
POST /v1/images/generate
{
"intent": "text-to-image-fast", // ← we'll pick the cheapest qualified model
"prompt": "a quiet sunrise over Mt Fuji"
}
# Or pin explicitly:
{ "model": "nano-banana-t2i", "prompt": "..." }SERVERLESS
GPU models
Hosted serverless GPU inference at /v1/gpu/{slug}. One API key, credit billing, audit log, and webhooks. Same wallet and dashboard as your LLM calls.
1. Pick a model
Browse the live catalog at /gpu-recommend. Each model lists its slug, per-call or per-second credit cost, and the maximum execution time per call.
2. Sync invocation (small jobs)
Short-running models return the output inline.
curl -X POST https://api.hypereal.cloud/v1/gpu/sdxl \
-H "Authorization: Bearer ck_..." \
-H "Content-Type: application/json" \
-d '{"input": {"prompt": "a tabby cat astronaut"}}'
→ { "id": "...",
"status": "succeeded",
"outputs": ["https://cdn.hypereal.cloud/gpu/.../out.png"],
"costCredits": 50,
"durationMs": 4210 }3. Async invocation (long jobs)
Long-running models queue and return a job id immediately with a 202. Poll, or wait for our cron + webhook poller to settle the job.
# Submit
POST /v1/gpu/wan-video
{ "input": { "prompt": "drone over Tokyo, neon, rain", "seconds": 5 } }
→ 202 { "id": "abc...", "status": "queued", "pollUrl": "/v1/gpu/jobs/abc..." }
# Poll
GET /v1/gpu/jobs/abc...
→ { "id": "abc...",
"status": "succeeded",
"outputs": ["https://cdn.hypereal.cloud/gpu/.../clip.mp4"],
"costCredits": 312,
"durationMs": 156000 }Failed and timed-out jobs auto-refund the credit reservation. Per-second billing reconciles on completion using the model's reported execution time, capped at the model'smaxSeconds.
ENTERPRISE
Teams, RBAC & SSO
Organizations, five built-in roles, SAML and OIDC single sign-on. Built so security and procurement can sign off without a custom rider.
Org-scoped keys, audit log, billing
Every API key, webhook, ComfyUI workflow, and GPU template can belong to an organization instead of an individual. Teammates share one budget, one audit trail, and one invoice. Personal keys keep working alongside.
POST /api/orgs
{
"name": "Acme Inc"
}
→ { id, slug, role: "owner" }Owner · Admin · Developer · Billing · Viewer
- Owner — everything, including delete-org
- Admin — manage members, keys, SSO, webhooks
- Developer — create/delete API keys, manage workflows + GPUs
- Billing — view + manage payments and audit log
- Viewer — read-only access to keys, billing, audit
Configure your IdP in 3 steps
- Create a SAML app in Okta / Azure AD / Auth0 / Google.
- Set ACS URL to
https://hypereal.cloud/api/auth/sso/<providerId> - Paste the IdP metadata XML into /settings/organization → SSO.
Set the email-domain claim (e.g. acme.com) and the login form will auto-route corporate emails to your IdP — no password prompt.
Issuer + client credentials
Drop in your issuer URL, client id, and client secret. We fetch the/.well-known/openid-configuration on save and surface a green check when the IdP is reachable.
POST /api/orgs/{id}/sso
{
"type": "oidc",
"issuer": "https://idp.acme.com",
"clientId": "...",
"clientSecret": "...",
"domain": "acme.com"
}12
Prețuri și credite
O unitate: 100 credite = $1.00 USD. LLM-urile facturează per token, folosind rata de input / output a fiecărui model. Modelele media facturează per imagine, per secundă sau per clip.
LLM-uri
Tokenuri × rata per MToken. Cererile de streaming sunt facturate pe baza ultimului chunk de utilizare.
Imagini
Sumă fixă per generare × n returnate efectiv.
Video și audio
Per secundă (majoritatea video), per clip (Veo, Vidu, Grok) sau per cerere (Fish Audio).
Claude, GPT, Gemini și anumite modele de imagine (GPT Image 2, Nano Banana) au prețuri stabilite de providerii direcți. Modelele video, audio și alte modele media sunt facturate la tarife standard.

