Change base_url and compare providers without reworking the call shape.
NextModel Turkiye · production gateway · OpenAI uyumlu
All models.One API.
AI API maliyetini Turkiye'deki ekipler icin tek bir OpenAI uyumlu hosted API ile yonetin. Misses gercek upstream'i cagirir, dogrulanmis Exact cache replay'leri indirimli faturalandirilir ve makbuzlar SDK entegrasyonunu yeniden yazmadan maliyeti gorunur tutar.
›prompt: "Bu workload icin bir model secin."
anclaude-sonnet-4-51.2s
maliyet: $0.00321
opgpt-4o-mini0.6s
maliyet: $0.00012
gogemini-2-5-flash0.5s
maliyet: $0.00008
dedeepseek-v30.9s
maliyet: $0.00037
Requests / sec42,891
Lowest input$0.112
Model sources42 / growing
Gateway statusOK
Kimler icin
Gercek API trafigi olan gelistiriciler ve kucuk ekipler icin tasarlandi.
Token maliyetini, tekrar eden istekleri ve entegrasyon hizini izliyorsaniz bu, mevcut SDK'nizin ustundeki hosted API katmanidir.
NextModel turns Fresh calls, exact-cache discounts, 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 Exact cache before traffic multiplies.
Each request can expose served mode, usage source, and receipt links.
Dogrudan yanit
NextModel nedir?
NextModel; model maliyeti buyumeden once Fresh fallback, Exact cache indirimleri ve seffaf makbuzlari tek yerde yonetmek isteyen gelistiriciler ve kucuk ekipler icin OpenAI uyumlu bir hosted API'dir.
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, exact-cache reuse, and receipts.
desteklenen model kaynaklari · resmi ortakliklar degildir
anAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshotanAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshot
neden nextmodel
Tek bir gateway.
Harcamayi, politikalari ve kaynaklari gorunur tutun.
Model secimini, butce kurallarini, kaynak karsilastirmasini ve kullanim raporlamasini uygulama kodunun disina alin. API tanidik kalir, karar katmani ise urun ve platform ekipleri icin gorunur hale gelir.
01 · one sdk
OpenAI SDK, many model sources.
Already using OpenAI? Change base_url, keep chat completions, streaming, tools, and JSON-oriented workflows.
pythonnodecurl
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=[...],
)02 · routing
Policies before production traffic.
Route by workload, source, budget, latency, or capability instead of scattering rules across services.
03 · billing
Spend by key, project, and team.
See which application paths drive token cost and turn model selection into an operational decision.
api.web$353 · 42%agent.eval$235 · 28%rag.ingest$151 · 18%dev$101 · 12%
04 · price
Compare the gap before calling.
05 · governance
Budget-aware model operations.
Bring your own keys, assign project limits, and keep a clear audit trail for model API spend.
42 models
tracked dimensionsproject · key · source
policy layerbudgets · providers
SDK modeOpenAI-compatible
06 · regions
Domestic + global, one endpoint.
Compare Chinese and global model sources from one interface without implying official provider partnership.
canli model grafigi
42 model,
tek bir shortlist.
Model karsilastirmasi icin tek bir endpoint. Uretim trafigini route etmeden once fiyat, tahmini gecikme, provider kaynagi ve workload uyumunu inceleyin.
Quickstart
Three steps from an existing SDK to visible spend control.
Issue a key for the project, environment, or workload you want to track.
Set the OpenAI SDK base URL to https://api.nextmodel.app/v1.
Use a model ID from the catalog, then compare cost and output quality.
Maliyet yonetisimi
Harcamalar buyumeden once Fresh, cache ve makbuzlari gorunur tutun.
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 safely replayed.
Transparent workflows
- Send requests through one OpenAI-compatible interface.
- Misses call the real upstream model.
- Exact cache hits are replayed with discounted billing.
- Use receipts and usage exports to reconcile what happened.
Docs CTA
Copy a working request in Python, Node, or curl.
Python
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.nextmodel.app/v1"
)
resp = client.chat.completions.create(
model="doubao-seed-2-0-mini",
messages=[{"role": "user", "content": "Hello from NextModel"}]
)
print(resp.choices[0].message.content)Node
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.NEXTMODEL_API_KEY,
baseURL: "https://api.nextmodel.app/v1",
});
const response = await client.chat.completions.create({
model: "doubao-seed-2-0-mini",
messages: [{ role: "user", content: "Hello from NextModel" }],
});
console.log(response.choices[0].message.content);curl
curl https://api.nextmodel.app/v1/chat/completions \
-H "Authorization: Bearer $NEXTMODEL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "doubao-seed-2-0-mini",
"messages": [{"role": "user", "content": "Hello from NextModel"}]
}'New benchmark
Before you enable caching, measure whether reuse is safe.
CacheSafety Bench checks safe hit rate, bad hit rate, semantic trap failures, and cost savings before teams trust a cache layer.
CacheSafety Bench helps teams compare safe hit rate, bad hit rate, semantic trap failures, and cost savings before they trust a cache layer in production.
Explore benchmarkSimdi baslayin
Pick the model, then govern the spend.
Open quickstart, copy a request, and compare your real workload against Fresh and Exact cache pricing.