Change base_url and compare providers without reworking the call shape.
All models.One API.
Ridte naklady na AI API pres jedno hosted API kompatibilni s OpenAI pro ceske tymy. Missy volaji skutecny upstream, zasahy upstream cache se uctuji 1:1 podle oficialni cache ceny a potvrzeni drzi vydaje viditelne bez prepisovani integrace SDK.
Latest
New model · 2026-09-05
GPT-6 Astra is live on NextModel — 1M context, tiered pricing
Pricing · 2026-09-05
The 272K cliff, explained: GPT-6 Astra pricing with worked examples
Migration · 2026-09-05
Migrating from GPT-5.x to GPT-6 Astra: ids, Responses API, rollback
Community · 2026-09-06
What early testers are actually doing with GPT-6 Astra
Pro koho
Navrzeno pro vyvojare a male tymy se skutecnym API provozem.
Pokud sledujete naklady na tokeny, opakovane requesty a rychlost integrace, toto je vrstva hosted API nad vasim stavajicim SDK.
NextModel turns Fresh calls, upstream cache pricing passed through 1:1, and receipts into one visible control layer above the SDK. That gives developers a place to keep unit economics honest and adopt a hosted API without reworking the app.
See the difference between Fresh and cached pricing before traffic multiplies.
Every request's receipt is hashed, batch-anchored on-chain, and independently verifiable.
Prime vysvetleni
Co je NextModel?
NextModel je hosted API kompatibilni s OpenAI pro vyvojare a male tymy, ktere chteji ridit Fresh fallback, ceny upstream cache 1:1 a pruhledna potvrzeni driv, nez narostou naklady na modely.
Teams use NextModel when they want a compatible hosted API without losing visibility into billing facts. The gateway keeps the familiar OpenAI SDK shape while adding transparent pricing context, upstream cache pass-through, and receipts.
Jedna brana.
Drzte naklady, politiky a zdroje na ocich.
Vyneste volbu modelu, pravidla rozpoctu, srovnani zdroju a reporting vyuziti z aplikacniho kodu. API zustava zname, zatimco rozhodovaci vrstva je viditelna pro produktove i platformni tymy.
OpenAI SDK, many model sources.
Already using OpenAI? Change base_url, keep chat completions, streaming, tools, and JSON-oriented workflows.
client = OpenAI(
base_url="https://api.nextmodel.app/v1",
api_key=os.environ["NM_KEY"],
)
client.chat.completions.create(
model="claude-sonnet-4-5",
messages=[...],
)Policies before production traffic.
Route by workload, source, budget, latency, or capability instead of scattering rules across services.
Spend by key, project, and team.
See which application paths drive token cost and turn model selection into an operational decision.
Compare the gap before calling.
Budget-aware model operations.
Bring your own keys, assign project limits, and keep a clear audit trail for model API spend.
Domestic + global, one endpoint.
Compare Chinese and global model sources from one interface without implying official provider partnership.
140 modelu,
jeden shortlist.
Jeden endpoint pro porovnani modelu. Zkontrolujte cenu, odhad latence, zdroj providera a shodu s workloadem driv, nez pustite produkcni provoz.
Rychly start
Tri kroky od stavajiciho SDK k viditelne kontrole nakladu.
Vydejte klic pro projekt, prostredi nebo pracovni zatez, kterou chcete sledovat.
Nastavte zakladni URL adresu OpenAI SDK na https://api.nextmodel.app/v1.
Pouzijte ID modelu z katalogu a poté porovnejte naklady a kvalitu vystupu.
Rizeni nakladu
Udrzte Fresh, cache a potvrzeni viditelne driv, nez vydaje porostou.
This is the layer developers and small teams need once request volume and spend start to grow.
Understand which applications and environments are driving model spend.
See which requests hit the real upstream and which were served as idempotent replays.
Transparent workflows
- Send requests through one OpenAI-compatible interface.
- Misses call the real upstream model.
- Upstream prompt-cache hits are billed 1:1 at official cached rates.
- Use receipts and usage exports to reconcile what happened.
CTA dokumentace
Zkopirujte funkcni pozadavek v Pythonu, Node nebo curl.
curl https://api.nextmodel.app/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $NEXTMODEL_API_KEY" \
-d '{"model":"qwen/qwen3.7-max","messages":[{"role":"user","content":"Reply with OK."}]}'# pip install openai
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["NEXTMODEL_API_KEY"],
base_url="https://api.nextmodel.app/v1",
)
resp = client.chat.completions.create(
model="qwen/qwen3.7-max",
messages=[{"role": "user", "content":"Reply with OK."}],
)
print(resp.choices[0].message.content)// npm install openai
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.NEXTMODEL_API_KEY,
baseURL: "https://api.nextmodel.app/v1",
});
const resp = await client.chat.completions.create({
model: "qwen/qwen3.7-max",
messages: [{ role: "user", "content":"Reply with OK." }],
});
console.log(resp.choices[0].message.content);Novy benchmark
Nez povolite cache, zmerte, zda je opakovane pouziti bezpecne.
CacheSafety Bench kontroluje mira bezpecnych zasahu, mira spatnych zasahu, selhani semantickych pasti a uspory nakladu, nez tymy zacnou duverovat vrstve cache.
CacheSafety Bench pomaha tymum porovnat miru bezpecnych zasahu, miru spatnych zasahu, selhani semantickych pasti a uspory nakladu, nez zacnou v produkci duverovat vrstve cache.
Prozkoumat benchmarkZacnete ted
Vyberte model a pote ridte vydaje.
Otevrete rychly start, zkopirujte pozadavek a porovnejte svou skutecnou zatez s cenami Fresh a upstream cache.