The intelligent layer for AI

Every prompt deserves
the right model.

Valefront is an LLM router: one OpenAI-compatible API that routes each request to a suitable model across providers by task, quality, cost, and latency, with automatic fallbacks. It is also Anthropic-compatible: point either SDK at https://llm.valefront.com.

Start building Explore the docs
your applicationPOST /v1/chat/completions
{ "model": "auto",
  "messages": [{ "role": "user", "content": "Summarize this call" }] }
Valefront markMint rounded-square outline with a blue and mint dotted cross and blue center diamond.
ValefrontROUTING ENGINE
illustrative routingEXAMPLE
BytePlus Seed logoSeed 2.0 LiteBytePlus
DeepSeek V4 FlashBytePlus
Dola Seed 2.0 MiniBytePlus
INTENT · QUALITY · COST · LATENCY — ROUTED IN REAL TIME
Meet your AI control plane

Smarter routing.
Less work for your team.

Stop hardcoding model choices. Valefront understands what each request needs and routes it across your stack with the right balance of quality, speed, and spend.

Route with intent

Match each prompt to the model that handles its complexity, context, and format best. Set your rules once; adapt as your needs change.

Make every token count

Choose the lowest-cost model that meets your quality bar. Keep premium models for the moments that need them.

Stay resilient by default

Automatic fallbacks keep your product responsive when a provider slows down or an endpoint goes offline.

Built for your stack

One endpoint.
Your whole model stack.

Keep the API you know. Point your app at Valefront and switch, compare, or combine providers without rewriting your integration.

Read the quickstart
OpenAI-compatible · Anthropic (Messages)
# OpenAI-compatible
curl https://llm.valefront.com/v1/chat/completions \
  -H 'Authorization: Bearer $VALEFRONT_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"model":"auto","messages":[{"role":"user","content":"Hello"}]}'

# Anthropic (Messages)
curl https://llm.valefront.com/v1/messages \
  -H 'x-api-key: $VALEFRONT_KEY' \
  -H 'anthropic-version: 2023-06-01' \
  -H 'Content-Type: application/json' \
  -d '{"model":"seed-2-0-lite-260428","max_tokens":64,"messages":[{"role":"user","content":"Hello"}]}'

const ai = new OpenAI({
  baseURL: 'https://llm.valefront.com/v1',
  apiKey: process.env.VALEFRONT_KEY,
});

const answer = await ai.chat.completions.create({
  model: 'auto',  // Valefront picks the right fit
  messages: [{ role: 'user', content: prompt }],
});
Frequently asked questions

Clear answers about Valefront.

What is Valefront?

Valefront is an LLM router that provides one OpenAI-compatible API for sending requests to suitable models across providers.

How does routing choose a model?

Routing considers the request's task, quality requirements, cost, and latency, then selects a suitable model and can use automatic fallbacks.

Which providers are supported?

Valefront routes across the providers implemented by the service; current provider availability is shown in the dashboard.

Is the API OpenAI-compatible?

Yes. Valefront provides an OpenAI-compatible API so compatible applications can use one endpoint.

Does Valefront support Anthropic Messages?

Yes. Valefront is OpenAI-compatible and Anthropic-compatible: point either SDK at https://llm.valefront.com.

How do I start?

Use the Valefront dashboard to get started, then point your application at the Valefront API base URL.

How much does Valefront cost?

Pay as you go, with no markup: you pay exactly the official price each model provider charges, per token. New accounts get free tokens to start. Live prices per model are on the dashboard.

Open to everyone · no card needed

Start building in minutes.

Create a free account and get 1,000,000 free tokens, plus 4,000,000 more after your first top-up, for 30 days. Then pay each provider’s official price, with no markup.

  1. 1Sign up on the dashboard
  2. 2Copy your API key
  3. 3Point your SDK at Valefront
Get your free API key Read the quickstart
app.py
from openai import OpenAI

client = OpenAI(
    base_url="https://llm.valefront.com/v1",
    api_key="vf_...",
)
reply = client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Hello"}],
)
Two lines change. Everything else stays.
Are you a model provider? Put your models in front of developers across Vietnam and Southeast Asia through one API.
Partner with Valefront →