Change base_url and compare providers without reworking the call shape.
NextModel Ελλαδα · production gateway · συμβατο με OpenAI
All models.One API.
Ελεγξτε το κοστος AI API με ενα hosted API συμβατο με OpenAI για ομαδες στην Ελλαδα. Τα misses καλουν το πραγματικο upstream, τα επαληθευμενα replay Exact cache χρεωνονται με εκπτωση και οι αποδειξεις κρατουν ορατη τη δαπανη χωρις να ξαναγραφτει η SDK ενσωματωση.
›prompt: "Dialekste ena montelo gia auto to workload."
anclaude-sonnet-4-51.2s
kostos: $0.00321
opgpt-4o-mini0.6s
kostos: $0.00012
gogemini-2-5-flash0.5s
kostos: $0.00008
dedeepseek-v30.9s
kostos: $0.00037
Requests / sec42,891
Lowest input$0.112
Model sources42 / growing
Gateway statusOK
Για ποιους ειναι
Φτιαγμενο για developers και μικρες ομαδες με πραγματικη κινηση API.
Αν παρακολουθειτε το κοστος token, τα επαναλαμβανομενα αιτηματα και την ταχυτητα ενσωματωσης, αυτο ειναι το hosted API στρωμα πανω απο το υπαρχον SDK σας.
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.
Αμεση απαντηση
Τι ειναι το NextModel;
Το NextModel ειναι ενα hosted API συμβατο με OpenAI για developers και μικρες ομαδες που θελουν να διαχειριζονται Fresh fallback, εκπτωσεις Exact cache και διαφανεις αποδειξεις πριν μεγαλωσει το κοστος των μοντελων.
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.
ypostirizomenes piges montelon · oxi episimes synergasties
anAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshotanAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshot
giati nextmodel
Ena gateway.
Kratiste orata exoda, politikes kai piges.
Vgalte tin epilogi montelou, tous kanones budget, ti sygkrisi pigon kai to reporting xrisis exo apo ton kodika tis efarmogis. To API menei gnosto, eno to epipedo apofaseon ginetai orato stis omades product kai platform.
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.
zontano grafima montelon
42 montela,
ena shortlist.
Ena mono endpoint gia sygkrisi montelon. Deite timi, ektimisi kathysterisis, pigi provider kai tairiasma me to workload prin kanei routing to production traffic.
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.
Διακυβερνηση κοστους
Κρατηστε Fresh, cache και αποδειξεις ορατα πριν αυξηθει η δαπανη.
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 benchmarkXekinise tora
Pick the model, then govern the spend.
Open quickstart, copy a request, and compare your real workload against Fresh and Exact cache pricing.