Hypereal API nuoroda
Vienas ck_ API raktas su prefiksu. OpenAI suderinama REST. Įdiekite į Claude Code, Codex CLI, Cursor, OpenAI SDK, Anthropic SDK arba tiesiogiai naudokite su curl. Pokalbiai, vaizdai, vaizdo įrašai, garsas, kodo agentai — viskas per vieną bazinį URL.
01 · Pradėkite per 90 s
Greita pradžia
Papildykite raktą, nukreipkite klientą į hypereal.cloud, ir paleiskite. Autentifikacija ir užklausų formos suderinamos su OpenAI — dauguma SDK veiks pakeitus tik bazinį URL.
Papildykite bent $2 (200 kreditų) ir sukurkite raktą /manage-api-keys. Raktai prasideda ck_.
Bazinė URL: https://hypereal.cloud/api/v1
Autentifikacijos antraštė yra Authorization: Bearer ck_.... Ta pati OpenAI užklausų struktūra, kurią jau žinote.
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
Autentifikacija
Kiekvienai užklausai reikia ck_ prefiksu prasidedančio rakto. Trys priimtini antraščių formatai tinka visiems SDK.
Bearer ck_... — naudojama OpenAI SDK, Codex CLI ir Cursor.ck_... — naudojama Anthropic SDK ir Claude Code /v1/messages.ck_... — Google Gemini SDK / natyvi forma, priimama /v1/gemini.?key=ck_... taip pat veikia.03 · Suderinama su OpenAI
Chat Completions
Pagrindinis galinis taškas. OpenAI Chat Completions wire formatas. Naudojamas GPT, Gemini, Qwen, DeepSeek, GLM ir visiems kitiems ne-Anthropic LLM.
/api/v1/chat/completionsUžklausos turinys
/v1/messages .role, content).false. SSE srautas, kai true; naudojimas įtraukiamas į galutinį bloką.Kainodara
Apmokestinama už žetoną pagal kiekvieno modelio įvesties / išvesties tarifą. 100 kreditų = $1.00. Minimalus likutis, norint kviesti galinį tašką, yra 200 kreditų ($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 ir tiekėjams suderinami modeliai
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 · Suderinama su Anthropic
Messages
Anthropic /v1/messages wire formatas su išplėstiniu mąstymu, kelių upstream perjungimu ir 15 s SSE palaikymo signalais. Naudokite Claude Code, OpenCode, OpenClaw ir oficialiam Anthropic SDK.
/api/v1/messagesUžklausos turinys
claude-sonnet-4-6, claude-opus-4-6, arba claude-haiku-4-5. Senesni Anthropic ID (claude-sonnet-4-5-20250929, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022) automatiškai priskiriami naujausiems atitikmenims.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 ribojamas samprotavimo pėdsakas. Galinis taškas siunčia 15 s SSE ping'us, kad tarpiniai serveriai neuždarytų ilgų mąstymo srautų.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 modeliai
claude-opus-4-6claude-sonnet-4-6claude-haiku-4-505 · OpenAI Responses API
Responses
Naujesnė OpenAI Responses API (naudojama Codex CLI `wire_api = responses` režime ir OpenAI Agents SDK). Ta pati autentifikacija kaip chat/completions; užklausos turinyje vietoje `messages` naudojamas `input`.
/api/v1/responsesPastabos
- Anthropic modeliai grąžina 400 — jie priklauso
/v1/messages. - Tiek transliuojamos, tiek netransliuojamos užklausos apmokestinamos pagal
response.usage.input_tokens/output_tokens. - Kai kurie upstream visada siunčia SSE — galinis taškas tai aptinka ir transliuoja sklandžiai, net jei
stream:false. - Kelių upstream perjungimas. Nustatykite ilgą kliento timeout (300 s+).
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 optimizuoti modeliai
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 nukreipia savo `wire_api = responses` tiekėją į /api/v1/responses. CLI prie bazinio URL prideda `/responses`, todėl bazinį URL sukonfigūruokite taip, kaip parodyta.
/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"
Tada eksportuokite savo raktą:export HYPEREAL_API_KEY=ck_...
Paleiskite codex įprastai. Viskas, ką siunčia Codex — pilni mąstymo srautai, įrankių iškvietimai, failų redagavimai — perduodama per proxy nepakitusi. Atsiskaitymas remiasi standartiniu input_tokens / output_tokens naudojimo bloku.
Tokia pati sąranka veikia OpenCode, Claude Code (naudokite /v1/messages), Cursor (naudokite /v1/chat/completions), ir Gemini CLI (naudokite /v1/gemini).
07
Vaizdų generavimas
OpenAI suderinama /images/generations forma. Sinchroninis — galinis taškas grąžina vaizdų URL (arba base64), kai upstream baigia darbą. Apmokestinama už vaizdą; `n` apribojamas nuo 1 iki 10.
/api/v1/images/generationsUžklausos turinys
image, reference_images).1024x1024, 1536x1024. Priklauso nuo teikėjo.creditsPerGeneration × n, galutinis taškas grąžina 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"
]
}'Vaizdų modeliai
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 · ilgai vykdoma
Vaizdo įrašų generavimas
Asinchroninis vaizdo įrašų galinis taškas — sukurkite užduotį, tada tikrinkite grąžintą užduoties URL, kol klipas bus paruoštas. Daugeliui modelių atsiskaitymas vyksta pagal sekundes, o tokiems modeliams kaip Gemini Omni Flash, Veo, Vidu ir Grok — pagal klipą.
/api/v1/videos/generateUžklausos turinys
per_second modeliams.16:9, 9:16, 1:1. Priklauso nuo teikėjo.Gemini Omni Flash accepts 16:9 or 9:16.720P.last_image_url arba image — žr. to modelio upstream dokumentaciją.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 mp4Vaizdo įrašų modeliai
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
Garsas — TTS, balso klonavimas, ASR
Trys modelio ID naudoja vieną galinį tašką. Užklausos kūnas ir atsakymas priklauso nuo to, kurį naudojate. Teikėjas yra Fish Audio (kviečiamas tiesiogiai, ne per ToAPI), apmokestinama už užklausą.
/api/v1/audio/generationsaudio-tts ir audio-clone.audio-asr (įvestis) ir audio-clone (referencinis balsas ≥ 10 s).data: [{ url }] TTS / klonavimui, text (+ pasirinktinai segments, duration) 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"
}'Garso modeliai
audio-ttsaudio-cloneaudio-asr10 · Google native shape
Gemini
Viename galiniame taške priimamos ir Gemini-native (`contents` / `generationConfig` / `systemInstruction`), ir OpenAI formos. Galinis taškas viduje konvertuoja į OpenAI formą prieš perduodamas toliau. Daugeliu atvejų paprasčiau naudoti /v1/chat/completions su Gemini modelio ID.
/api/v1/geminitemperature, maxOutputTokens, ir t. t.contents.Autentifikacijos antraštė: x-goog-api-key: ck_..., ?key=ck_...arba Authorization: Bearer ck_... visi veikia.
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 modeliai
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
Klaidos ir užklausų limitai
Visos klaidos yra JSON formatu '{ error: { type, message } }'. Užklausų limitai vertinami pagal vartotoją, ne pagal raktą — keli raktai dalijasi ta pačia kvota.
ck_ prefikso), nebegaliojantis arba neaktyvus raktas.X-RateLimit-Limit, X-RateLimit-Remainingir X-RateLimit-Reset antraštės grąžinamos, kai pasiekiamas užklausų limitas.model, nežinomas modelio ID (atsakyme yra available_models), arba netinkamas galinis taškas formatui (pvz., Anthropic modelis /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
Kainodara ir kreditai
Viena vienetė: 100 kreditų = $1.00 USD. LLM atsiskaitomi pagal žetonus, naudojant kiekvieno modelio įvesties / išvesties tarifą. Medijos modeliai atsiskaitomi už vaizdą, už sekundę arba už klipą.
LLM
Žetonai × kaina už PMtok. Srautinių užklausų apmokestinimas skaičiuojamas pagal galutinį naudojimo bloką.
Vaizdai
Fiksuota kaina už generavimą × faktiniai n grąžinti.
Vaizdo įrašai ir garsas
Pagal sekundę (dauguma vaizdo įrašų), už klipą (Veo, Vidu, Grok) arba už užklausą (Fish Audio).
Claude, GPT, Gemini ir atrinkti vaizdų modeliai (GPT Image 2, Nano Banana) kainuoja pagal tiesioginių teikėjų tarifus. Vaizdo įrašų, garso ir kiti medijos modeliai apmokestinami standartiniais tarifais.

