Change base_url and compare providers without reworking the call shape.
NextModel Brasil · gateway de producao · compativel com OpenAI
All models.One API.
Controle o gasto com AI API usando uma API hospedada compativel com OpenAI para equipes no Brasil. Misses chamam o upstream real, replays Exact cache verificados sao cobrados com desconto e os recibos mantem a despesa visivel sem reescrever sua integracao SDK.
›prompt: "Escolha um modelo para este workload."
anclaude-sonnet-4-51.2s
custo: $0.00321
opgpt-4o-mini0.6s
custo: $0.00012
gogemini-2-5-flash0.5s
custo: $0.00008
dedeepseek-v30.9s
custo: $0.00037
Requests / sec42,891
Lowest input$0.112
Model sources42 / growing
Gateway statusOK
Para quem e
Feito para desenvolvedores e equipes pequenas com trafego API real.
Se voce acompanha custo por token, chamadas repetidas e velocidade de integracao, esta e a camada de API hospedada acima do seu SDK atual.
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.
Resposta direta
O que e NextModel?
NextModel e uma API hospedada compativel com OpenAI para desenvolvedores e equipes pequenas que querem administrar Fresh fallback, descontos Exact cache e recibos transparentes antes que o gasto com modelos escale.
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.
fontes de modelos suportadas · nao sao parcerias oficiais
anAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshotanAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshot
por que nextmodel
Um gateway.
Mantenha gasto, politicas e fontes visiveis.
Tire escolha de modelo, regras de orcamento, comparacao de fontes e relatorios de uso do codigo da aplicacao. A API continua familiar enquanto a camada de decisao fica visivel para produto e plataforma.
01 · um sdk
OpenAI SDK, muitas fontes de modelo.
Ja usa OpenAI? Mude o base_url e mantenha chat completions, streaming, tools e fluxos orientados a JSON.
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
Politicas antes do trafego de producao.
Faça routing por carga, fonte, orcamento, latencia ou capacidade em vez de espalhar regras por servicos.
03 · billing
Custo por key, projeto e equipa.
Veja que caminhos da aplicacao puxam o custo de tokens e transforme a escolha de modelo numa decisao operacional.
api.web$353 · 42%agent.eval$235 · 28%rag.ingest$151 · 18%dev$101 · 12%
04 · preco
Compare a diferenca antes de chamar.
05 · governance
Operacao de modelos com consciencia de orcamento.
Traga as suas proprias keys, atribua limites por projeto e mantenha um trilho claro para o gasto em APIs de modelos.
42 modelos
dimensoes acompanhadasprojeto · key · fonte
camada de politicaorcamentos · fornecedores
modo SDKcompativel com OpenAI
06 · regioes
China + global, um endpoint.
Compare fontes de modelos chineses e globais a partir de uma unica interface sem insinuar parceria oficial.
grafo ao vivo de modelos
42 modelos,
uma shortlist.
Um unico endpoint para comparacao de modelos. Confira preco, estimativa de latencia, origem do provedor e aderencia ao workload antes de roteirizar trafego de producao.
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.
Governanca de custos
Mantenha Fresh, cache e recibos visiveis antes de o gasto crescer.
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 benchmarkComece agora
Pick the model, then govern the spend.
Open quickstart, copy a request, and compare your real workload against Fresh and Exact cache pricing.