Hypereal API atsauce
Viena ck_ prefiksēta API atslēga. OpenAI saderīgs REST. Ievietojiet Claude Code, Codex CLI, Cursor, OpenAI SDK, Anthropic SDK vai izsauciet tieši ar curl. Čats, attēli, video, audio, koda aģenti — viss aiz viena bāzes URL.
01 · Sāciet 90 s laikā
Ātra sākšana
Papildiniet atslēgu, norādiet klientu uz hypereal.cloud, un sāciet. Autentifikācija un pieprasījumu formāti ir saderīgi ar OpenAI — lielākā daļa SDK strādā, mainot tikai bāzes URL.
Papildiniet vismaz par $2 (200 kredīti) un izveidojiet atslēgu vietnē /manage-api-keys. Atslēgas sākas ar ck_.
Bāzes URL: https://hypereal.cloud/api/v1
Autentifikācijas galvene ir Authorization: Bearer ck_.... Tie paši OpenAI pieprasījumu ķermeņi, ko jau pazīstat.
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
Autentifikācija
Katram pieprasījumam ir nepieciešama ck_ prefiksēta atslēga. Trīs atbalstītie galvenes formāti aptver visus SDK.
Bearer ck_... — izmanto OpenAI SDK, Codex CLI un Cursor.ck_... — izmanto Anthropic SDK un Claude Code vietnē /v1/messages.ck_... — Google Gemini SDK / vietējais formāts, pieņem arī /v1/gemini.?key=ck_... darbojas.03 · Saderīgs ar OpenAI
Chat Completions
Darba zirga galapunkts. OpenAI Chat Completions datu formāts. Izmanto GPT, Gemini, Qwen, DeepSeek, GLM un jebkuram citam ne-Anthropic LLM.
/api/v1/chat/completionsPieprasījuma ķermenis
/v1/messages .role, content).false. SSE straume, ja true; lietojums ir iekļauts pēdējā fragmentā.Cenrādis
Maksa tiek aprēķināta par tokeniem, izmantojot katra modeļa ievades/izvades likmi. 100 kredīti = $1.00. Minimālais atlikums galapunkta izsaukšanai ir 200 kredīti ($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 un pakalpojumu sniedzējiem saderīgi modeļi
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 · Saderīgs ar Anthropic
Ziņojumi
Anthropic /v1/messages datu formāts ar paplašināto domāšanu, vairāku augšupējo avotu kļūmjpārlēdi un 15 sekunžu SSE uztursignāliem. Lietojiet Claude Code, OpenCode, OpenClaw un oficiālajam Anthropic SDK.
/api/v1/messagesPieprasījuma ķermenis
claude-sonnet-4-6, claude-opus-4-6, vai claude-haiku-4-5. Vecāki Anthropic ID (claude-sonnet-4-5-20250929, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022) automātiski tiek piesaistīti jaunākajiem ekvivalentiem.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 ierobežo spriešanas pēdu. Galapunkts sūta 15 s SSE pingus, lai starpniekserveri nenoslēgtu ilgās domāšanas straumes.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 modeļi
claude-opus-4-6claude-sonnet-4-6claude-haiku-4-505 · OpenAI Responses API
Responses
OpenAI jaunākā Responses API (to izmanto Codex CLI `wire_api = responses` režīmā un OpenAI Agents SDK). Tāda pati autentifikācija kā chat/completions; pieprasījuma ķermenī `messages` vietā tiek lietots `input`.
/api/v1/responsesPiezīmes
- Anthropic modeļi atgriež 400 — tie jālieto sadaļā
/v1/messages. - Straumēšana un neraumēšana tiek apmaksāta, balstoties uz
response.usage.input_tokens/output_tokens. - Daži augšupējie avoti vienmēr izvada SSE — galapunkts to nosaka un caurraida straumi caurspīdīgi pat tad, ja
stream:false. - Vairāku augšupējo avotu kļūmjpārlēde. Iestatiet garu klienta noildzi (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 optimizētie modeļi
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 norāda savu `wire_api = responses` pakalpojumu sniedzēju uz /api/v1/responses. CLI pievieno `/responses` bāzes URL galam, tāpēc konfigurējiet bāzes URL, kā parādīts.
/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"
Tad eksportējiet savu atslēgu:export HYPEREAL_API_KEY=ck_...
Palaidiet codex kā parasti. Viss, ko Codex nosūta — pilnas spriešanas straumes, rīku izsaukumi, failu labojumi — tiek caurvīts nemainīts. Norēķini balstās uz standarta input_tokens / output_tokens lietošanas bloku.
Tāda pati iestatīšana darbojas OpenCode, Claude Code (izmantojiet /v1/messages), Cursor (izmantojiet /v1/chat/completions), un Gemini CLI (izmantojiet /v1/gemini).
07
Attēlu ģenerēšana
OpenAI saderīgs /images/generations formāts. Sinhrons — galapunkts atgriež attēlu URL (vai base64), kad augšupējais pakalpojums pabeidz darbu. Maksa tiek aprēķināta par attēlu; `n` tiek ierobežots līdz 1–10.
/api/v1/images/generationsPieprasījuma ķermenis
image, reference_images).1024x1024, 1536x1024. Atkarīgs no pakalpojuma sniedzēja.creditsPerGeneration × n, galapunkts atgriež 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"
]
}'Attēlu modeļi
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 · ilgstošs
Video ģenerēšana
Asinhrons video galapunkts — izveidojiet darbu, pēc tam aptaujājiet atgriezto darba URL, līdz klips ir gatavs. Norēķini daudziem modeļiem notiek par sekundi vai par klipu tādiem modeļiem kā Gemini Omni Flash, Veo, Vidu un Grok.
/api/v1/videos/generatePieprasījuma ķermenis
per_second modeļiem.16:9, 9:16, 1:1. Atkarīgs no pakalpojuma sniedzēja.Gemini Omni Flash accepts 16:9 or 9:16.720P.last_image_url vai image — skatiet attiecīgā modeļa augšupējās dokumentācijas.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 mp4Video modeļi
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, balss klonēšana, ASR
Trīs modeļu ID izmanto vienu galapunktu. Pieprasījuma un atbildes forma ir atkarīga no tā, kuru izmantojat. Pakalpojuma sniedzējs ir Fish Audio (izsaukts tieši, nevis caur ToAPI), norēķini notiek par pieprasījumu.
/api/v1/audio/generationsaudio-tts un audio-clone.audio-asr (ievade) un audio-clone (atsauces balss ≥ 10 s).data: [{ url }] TTS / klonēšanai, text (+ izvēles 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"
}'Audio modeļi
audio-ttsaudio-cloneaudio-asr10 · Google native shape
Gemini
Pieņem gan Gemini-native (`contents` / `generationConfig` / `systemInstruction`), gan OpenAI formas vienā un tajā pašā galapunktā. Galapunkts iekšēji pārveido uz OpenAI formu pirms pārsūtīšanas tālāk. Lielākajai daļai koda /v1/chat/completions ar Gemini modeļa ID ir vienkāršāk.
/api/v1/geminitemperature, maxOutputTokens, utt.contents.Autentifikācijas galvene: x-goog-api-key: ck_..., ?key=ck_...vai Authorization: Bearer ck_... visi darbojas.
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 modeļi
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
Kļūdas un pieprasījumu limiti
Visas kļūdas ir JSON formā '{ error: { type, message } }'. Pieprasījumu limiti tiek vērtēti uz lietotāju, nevis uz atslēgu — vairākas atslēgas koplieto vienu un to pašu kvotu.
ck_ prefiksa), beigusies derīguma termiņš vai neaktīva atslēga.X-RateLimit-Limit, X-RateLimit-Remainingun X-RateLimit-Reset galvenes tiek atgrieztas pieprasījumu limita atbildēs.model, nezināms modeļa ID (atbildē ir available_models), vai nepareizs galapunkts formātam (piem., Anthropic modelis uz /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
Cenu noteikšana un kredīti
Viena vienība: 100 kredīti = $1.00 USD. LLM norēķini notiek par tokenu, izmantojot katra modeļa ievades / izvades likmi. Mediju modeļiem norēķini notiek par attēlu, par sekundi vai par klipu.
LLM
Tokeni × likme par MTok. Straumēšanas pieprasījumi tiek apmaksāti pēc gala lietojuma bloka.
Attēli
Fiksēta maksa par ģenerēšanu × faktiski n atgriezts.
Video un audio
Par sekundi (vairums video), par klipu (Veo, Vidu, Grok) vai par pieprasījumu (Fish Audio).
Claude, GPT, Gemini un atlasītie attēlu modeļi (GPT Image 2, Nano Banana) tiek cenoti tiešo pakalpojumu sniedzēju ietvaros. Video, audio un citi mediju modeļi tiek apmaksāti pēc standarta likmēm.

