Hypereal API-reference
Én ck_-præfikseret API-nøgle. OpenAI-kompatibel REST. Brug den direkte i Claude Code, Codex CLI, Cursor, OpenAI SDK'en, Anthropic SDK'en, eller kald den direkte med curl. Chat, billeder, video, audio, kodeagenter — alt bag én base-URL.
01 · Kom i gang på 90 sek.
Hurtigstart
Opret en nøgle, peg din klient mod hypereal.cloud, og ship. Auth og anmodningsformater er kompatible med OpenAI — de fleste SDK'er virker ved kun at ændre base-URL'en.
Fyld mindst $2 op (200 kreditter), og opret en nøgle på /manage-api-keys. Nøgler starter med ck_.
Base-URL: https://hypereal.cloud/api/v1
Auth-header er Authorization: Bearer ck_.... De samme OpenAI-anmodningsbodyer, du allerede kender.
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
Autentificering
Hver anmodning kræver en nøgle med præfikset ck_. Tre accepterede header-formater dækker alle SDK'er.
Bearer ck_... — bruges af OpenAI SDK, Codex CLI og Cursor.ck_... — bruges af Anthropic SDK og Claude Code på /v1/messages.ck_... — Google Gemini SDK / indfødt format, accepteret af /v1/gemini.?key=ck_... virker også.03 · Kompatibel med OpenAI
Chat-completions
Arbejdstesten. OpenAI Chat Completions wire format. Bruges til GPT, Gemini, Qwen, DeepSeek, GLM og alle andre ikke-Anthropic LLM'er.
/api/v1/chat/completionsAnmodningsbody
/v1/messages i stedet.role, content).false. SSE-stream, når true; brug er inkluderet i den sidste chunk.Prissætning
Afregnes per token baseret på hver models input/output-rate. 100 kreditter = $1.00. Minimumsbalancen for at kalde endpointet er 200 kreditter ($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 ?? '');
}OpenAI- og provider-kompatible modeller
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 · Kompatibel med Anthropic
Beskeder
Anthropic /v1/messages wire format med udvidet tænkning, failover på tværs af flere upstreams og 15-sekunders SSE keepalives. Brug dette til Claude Code, OpenCode, OpenClaw og det officielle Anthropic SDK.
/api/v1/messagesAnmodningsbody
claude-sonnet-4-6, claude-opus-4-6, eller claude-haiku-4-5. Ældre Anthropic-ID'er (claude-sonnet-4-5-20250929, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022) auto-aliases til de nyeste tilsvarende.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 begrænser reasoning-trace. Endpointet sender 15s SSE-pings for at forhindre proxies i at lukke lange thinking-streams.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);Anthropic-modeller
claude-opus-4-6claude-sonnet-4-6claude-haiku-4-505 · OpenAI Responses API
Responses
OpenAI's nyere Responses API (brugt af Codex CLI's `wire_api = responses`-tilstand og OpenAI Agents SDK). Samme auth som chat/completions; anmodningsbodyen bruger `input` i stedet for `messages`.
/api/v1/responsesNoter
- Anthropic-modeller returnerer en 400 — de hører til på
/v1/messages. - Streaming og non-streaming afregnes begge baseret på
response.usage.input_tokens/output_tokens. - Nogle upstreams sender altid SSE — endpointet registrerer dette og streamer videre transparent, selv hvis
stream:false. - Failover på tværs af flere upstreams. Sæt en lang client timeout (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);Codex-optimerede modeller
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 peger sin `wire_api = responses`-provider mod /api/v1/responses. CLI'en sætter `/responses` foran base-URL'en, så konfigurer base-URL'en som vist.
/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"
Eksportér derefter din nøgle:export HYPEREAL_API_KEY=ck_...
Kør codex som normalt. Alt, hvad Codex sender — fulde reasoning-streams, tool calls, filredigeringer — proxes videre uændret. Fakturering bruger den standard input_tokens / output_tokens -usage-block.
Samme opsætning virker til OpenCode, Claude Code (brug /v1/messages), Cursor (brug /v1/chat/completions), og Gemini CLI (brug /v1/gemini).
07
Billedgenerering
OpenAI-kompatibelt /images/generations-format. Synkront — endpointet returnerer billed-URL'er (eller base64), når upstreamen er færdig. Afregnes per billede; `n` begrænses til 1–10.
/api/v1/images/generationsAnmodningsbody
image, reference_images).1024x1024, 1536x1024. Afhænger af udbyderen.creditsPerGeneration × n, returnerer endpointet 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"
]
}'Billedmodeller
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 · langvarig
Videogenerering
Asynkront video-endpoint — opret et job, og poll derefter den returnerede job-URL, indtil klippet er klar. Fakturering sker pr. sekund for mange modeller eller pr. klip for modeller som Gemini Omni Flash, Veo, Vidu og Grok.
/api/v1/videos/generateAnmodningsbody
per_second modeller.16:9, 9:16, 1:1. Afhænger af udbyderen.Gemini Omni Flash accepts 16:9 or 9:16.720P.last_image_url eller image — se upstream-dokumentationen for den 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 mp4Videomodeller
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
Lyd — TTS, stemmekloning, ASR
Tre model-ID'er deler ét endpoint. Struktureringen af body og svar afhænger af, hvilken du kalder. Udbyderen er Fish Audio (kaldt direkte, ikke via ToAPI), faktureret pr. anmodning.
/api/v1/audio/generationsaudio-tts og audio-clone.audio-asr (input) og audio-clone (reference-stemme ≥ 10s).data: [{ url }] for TTS / clone, text (+ valgfri segments, duration) for 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"
}'Lydmodeller
audio-ttsaudio-cloneaudio-asr10 · Google native shape
Gemini
Accepterer både Gemini-native (`contents` / `generationConfig` / `systemInstruction`) og OpenAI-shapes på det samme endpoint. Endpointet konverterer internt til OpenAI, før det videresendes. For det meste kode er /v1/chat/completions med et Gemini model-ID enklere.
/api/v1/geminitemperature, maxOutputTokens, osv.contents.Auth-header: x-goog-api-key: ck_..., ?key=ck_..., eller Authorization: Bearer ck_... fungerer alle.
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());Gemini-modeller
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
Fejl & rategrænser
Alle fejl er JSON i formen '{ error: { type, message } }'. Rategrænser evalueres per bruger, ikke per nøgle — flere nøgler deler den samme kvote.
ck_ prefix), udløbet eller inaktiv nøgle.X-RateLimit-Limit, X-RateLimit-Remaining, og X-RateLimit-Reset headers returneres ved svar på rategrænser.model, ukendt model-ID (svaret inkluderer available_models), eller forkert endpoint til formatet (f.eks. en Anthropic-model på /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
Priser & kreditter
Én enhed: 100 kreditter = $1.00 USD. LLM'er faktureres pr. token ved brug af hver models input / output-rate. Mediemodeller faktureres pr. billede, pr. sekund eller pr. klip.
LLM'er
Tokens × per-MTok-rate. Streaminganmodninger faktureres ud fra den endelige usage-chunk.
Billeder
Fast pr. generering × faktisk n returneret.
Video & lyd
Pr. sekund (de fleste video), pr. klip (Veo, Vidu, Grok) eller pr. anmodning (Fish Audio).
Claude, GPT, Gemini og udvalgte billedmodeller (GPT Image 2, Nano Banana) er prissat under direkte udbydere. Video, lyd og andre mediemodeller faktureres til standardpriser.

