Change base_url and compare providers without reworking the call shape.
NextModel · production gateway · 42 model sources
All models.
One API.
Control AI API cost with one OpenAI-compatible gateway, built for teams already shipping AI products. Compare providers, route by workload, and keep spend visible without rewriting your SDK integration.
›prompt: "Pick a model for this workload."
anclaude-sonnet-4-51.2s
cost: $0.00321
opgpt-4o-mini0.6s
cost: $0.00012
gogemini-2-5-flash0.5s
cost: $0.00008
dedeepseek-v30.9s
cost: $0.00037
Requests / sec42,891
Lowest input$0.112
Model sources42 / growing
Gateway statusOK
Who it's for
Built for teams that already ship multi-model apps.
If you're comparing providers, watching token spend, or adding budgets and BYOK, this is the layer above your existing SDK.
NextModel turns model choice, routing, budgets, and BYOK into one visible control layer above the SDK. That gives product and platform teams a place to shortlist models, keep unit economics honest, and switch providers without reworking the app.
Budget by project, key, and team before traffic multiplies.
Keep domestic and global models in the same shortlist.
supported model sources · not official partnerships
anAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshotanAnthropicopOpenAIgoGooglevoVolcenginealAlibaba ClouddeDeepSeekopOpenRoutermoMoonshot
why nextmodel
One gateway.
More control over spend.
Keep model choice, budget rules, source comparison, and usage reporting out of application code. The API stays familiar while the decision layer becomes visible to product and platform teams.
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.
live model graph
42 models,
one shortlist.
One endpoint for model comparison. Inspect price, latency estimates, provider source, and workload fit before you route 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.
Model entrypoints
Start from the workload, not the vendor.
These entry pages help teams shortlist coding, Chinese, low-cost, vision, long-context, and agent models before committing traffic.
Coding
Shortlist model candidates for coding workloads.
Chinese
Shortlist model candidates for Chinese workloads.
Low cost
Shortlist model candidates for low-cost workloads.
Vision
Shortlist model candidates for vision workloads.
Long context
Shortlist model candidates for long-context workloads.
Agent
Shortlist model candidates for agent workloads.
Cost governance
Keep budgets, BYOK, teams, and reports visible before scale.
This is the layer product and platform teams use once model count and spend start to grow.
Understand which applications and environments are driving model spend.
Set budget expectations before product traffic multiplies request volume.
Governance workflows
- Route workloads through one OpenAI-compatible interface.
- Compare domestic and global providers by price and capability.
- Use BYOK for teams with existing provider accounts.
- Build monthly reports from usage and model pricing.
Featured models
Shortlist a few models before routing production traffic.
VolcengineProduction
Doubao Seed 2.0 Mini is the lowest-cost production model currently exposed through the NextModel public gateway. It is a practical default for Chinese Q&A, classification, summarization, and lightweight multimodal tasks.
Best forChinese Q&A, low-cost general chat, multimodal understanding
RoutingConfigured
Tool callingVisionJSON modeLong context
Platform curatedNextModel production gateway and Volcengine pricing config
AnthropicCatalog
Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
Best forcoding agents, code review, complex writing
RoutingConfigured
Tool callingJSON modeLong contextReasoning
OpenRouter if availableOpenRouter public Models API live metadata; public price comes from the registry pricing rule
OpenRouterCatalog
GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...
Best forlow-cost chat, image understanding, classification
RoutingConfigured
Tool callingVisionJSON modeLong context
OpenRouter if availableOpenRouter public Models API live metadata; public price comes from the registry pricing rule
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 benchmarkStart now
Pick the model, then govern the spend.
Open quickstart, copy a request, and compare your real workload against the catalog.