הפניה ל-API של Hypereal
מפתח API אחד עם קידומת ck_. REST תואם OpenAI. אפשר לשלב ב-Claude Code, Codex CLI, Cursor, ה-OpenAI SDK, ה-Anthropic SDK, או לקרוא לו ישירות עם curl. צ'אט, תמונות, וידאו, אודיו, סוכני קוד — הכול מאחורי כתובת Base אחת.
01 · תחילת עבודה ב-90 שניות
התחלה מהירה
צרו מפתח, כוונו את הלקוח שלכם אל hypereal.cloud, וקדמו לפרודקשן. האימות וצורות הבקשה תואמים ל-OpenAI — רוב ה-SDKs עובדים על ידי שינוי כתובת ה-base בלבד.
טענו לפחות $2 (200 קרדיטים) וצרו מפתח ב- /manage-api-keys. מפתחות מתחילים ב- ck_.
Base URL: https://hypereal.cloud/api/v1
כותרת האימות היא Authorization: Bearer ck_.... אותן בקשות OpenAI שאתם כבר מכירים.
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
אימות
כל בקשה צריכה מפתח שמתחיל ב-ck_. שלושה פורמטים נתמכים של כותרות מכסים את כל ה-SDKs.
Bearer ck_... — בשימוש על ידי OpenAI SDK, Codex CLI, ו-Cursor.ck_... — בשימוש על ידי Anthropic SDK ו-Claude Code על /v1/messages.ck_... — צורת Gemini SDK / native של Google, נתמך גם על ידי /v1/gemini.?key=ck_... עובד גם.03 · תואם OpenAI
Chat Completions
נקודת הקצה המרכזית. פורמט OpenAI Chat Completions. משמש עבור GPT, Gemini, Qwen, DeepSeek, GLM, וכל LLM אחר שאינו Anthropic.
/api/v1/chat/completionsגוף הבקשה
/v1/messages במקום.role, content).false. זרם SSE כאשר true; ה-usage כלול בחלק האחרון.תמחור
חיוב לפי טוקן לפי תעריפי הקלט/פלט של כל מודל. 100 קרדיטים = $1.00. היתרה המינימלית לקריאה לנקודת הקצה היא 200 קרדיטים ($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 ?? '');
}מודלים תואמי OpenAI וספקים
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 · תואם Anthropic
Messages
פורמט /v1/messages של Anthropic עם extended thinking, failover בין מספר upstreams, ו-keepalives של 15 שניות ב-SSE. השתמשו בזה עבור Claude Code, OpenCode, OpenClaw, וה-SDK הרשמי של Anthropic.
/api/v1/messagesגוף הבקשה
claude-sonnet-4-6, claude-opus-4-6, או claude-haiku-4-5. מזהי Anthropic ישנים (claude-sonnet-4-5-20250929, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022) ממופים אוטומטית לשקולים העדכניים ביותר.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 מגביל את מסלול ההסקה. נקודת הקצה שולחת פינגי SSE כל 15 שניות כדי למנוע מ-proxies לסגור זרמי thinking ארוכים.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);מודלי Anthropic
claude-opus-4-6claude-sonnet-4-6claude-haiku-4-505 · OpenAI Responses API
Responses
ה-Responses API החדש יותר של OpenAI (בשימוש על ידי מצב `wire_api = responses` של Codex CLI ו-OpenAI Agents SDK). אותו אימות כמו chat/completions; גוף הבקשה משתמש ב-`input` במקום `messages`.
/api/v1/responsesהערות
- מודלי Anthropic מחזירים 400 — הם שייכים ל-
/v1/messages. - גם streaming וגם non-streaming מחויבים לפי
response.usage.input_tokens/output_tokens. - חלק מה-upstreams תמיד פולטים SSE — נקודת הקצה מזהה זאת ומזרימה דרך transparently גם אם
stream:false. - Failover בין מספר upstreams. הגדירו timeout ארוך ללקוח (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);מודלים מכווני 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 מפנה את ספק `wire_api = responses` שלו אל /api/v1/responses. ה-CLI מוסיף `/responses` ל-base URL, לכן יש להגדיר את ה-base URL כפי שמוצג.
/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"
לאחר מכן export למפתח שלכם:export HYPEREAL_API_KEY=ck_...
הריצו את codex כרגיל. כל מה ש-Codex שולח — זרמי reasoning מלאים, קריאות tool, עריכות קבצים — עובר דרך הפרוקסי ללא שינוי. החיוב מתבסס על בלוק ה-standard input_tokens / output_tokens usage.
אותה הגדרה עובדת עבור OpenCode, Claude Code (השתמשו ב- /v1/messages), Cursor (השתמשו ב- /v1/chat/completions), ו-Gemini CLI (השתמשו ב- /v1/gemini).
07
יצירת תמונה
מבנה תואם OpenAI של /images/generations. סינכרוני — נקודת הקצה מחזירה כתובות URL של תמונות (או base64) כאשר ה-upstream מסיים. חיוב לפי תמונה; `n` מוגבל ל-1–10.
/api/v1/images/generationsגוף הבקשה
image, reference_images).1024x1024, 1536x1024. תלוי בספק.creditsPerGeneration × n, ה-endpoint מחזיר 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"
]
}'מודלי תמונה
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
יצירת וידאו
endpoint אסינכרוני לוידאו — יוצרים job, ואז מבצעים polling ל-URL של ה-job שהוחזר עד שהקליפ מוכן. החיוב הוא לפי שנייה עבור מודלים רבים או לפי קליפ עבור מודלים כמו Gemini Omni Flash, Veo, Vidu, ו-Grok.
/api/v1/videos/generateגוף הבקשה
per_second מודלים.16:9, 9:16, 1:1. תלוי בספק.Gemini Omni Flash accepts 16:9 or 9:16.720P.last_image_url או image — ראו את התיעוד של upstream עבור אותו מודל.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 mp4מודלי וידאו
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
אודיו — TTS, שיבוט קול, ASR
שלושה מזהי מודל חולקים endpoint אחד. המבנה של ה-body ושל ה-response תלוי בזה שנקרא. הספק הוא Fish Audio (נקרא ישירות, לא דרך ToAPI), והחיוב הוא לפי בקשה.
/api/v1/audio/generationsaudio-tts ו audio-clone.audio-asr (קלט) ו audio-clone (קול ייחוס ≥ 10s).data: [{ url }] עבור TTS / clone, text (+ אופציונלי segments, duration) עבור 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"
}'מודלי אודיו
audio-ttsaudio-cloneaudio-asr10 · Google native shape
Gemini
מקבל גם Gemini-native (`contents` / `generationConfig` / `systemInstruction`) וגם OpenAI shapes באותו endpoint. ה-endpoint ממיר ל-OpenAI פנימית לפני ההעברה הלאה. עבור רוב הקוד, /v1/chat/completions עם מזהה מודל של Gemini הוא פשוט יותר.
/api/v1/geminitemperature, maxOutputTokens, וכו'.contents.כותרת אימות: x-goog-api-key: ck_..., ?key=ck_..., או Authorization: Bearer ck_... כולם עובדים.
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());מודלי 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
שגיאות ומגבלות קצב
כל השגיאות הן JSON במבנה '{ error: { type, message } }'. מגבלות קצב נבדקות לפי משתמש, לא לפי מפתח — כמה מפתחות חולקים את אותה מכסה.
ck_ prefix), פג תוקף, או לא פעיל.X-RateLimit-Limit, X-RateLimit-Remaining, ו X-RateLimit-Reset headers מוחזרים בתגובות rate limit.model, מזהה מודל לא מוכר (התגובה כוללת available_models), או endpoint לא נכון עבור הפורמט (למשל מודל Anthropic על /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
תמחור וקרדיטים
יחידה אחת: 100 קרדיטים = $1.00 USD. LLMs מחויבים לפי token באמצעות תעריף הקלט / הפלט של כל מודל. מודלי מדיה מחויבים לפי תמונה, לפי שנייה, או לפי קליפ.
LLMs
טוקנים × תעריף לכל MTok. בקשות streaming מחויבות לפי ה-chunk הסופי של ה-usage.
תמונות
תשלום קבוע לכל יצירה × actual n שהוחזר.
וידאו ואודיו
לפי שנייה (רוב הווידאו), לפי קליפ (Veo, Vidu, Grok), או לפי בקשה (Fish Audio).
Claude, GPT, Gemini, ומודלי תמונה נבחרים (GPT Image 2, Nano Banana) מתומחרים מול ספקים ישירים. וידאו, אודיו, ומודלי מדיה אחרים מחויבים בתעריפים הסטנדרטיים.

