LATTIS INFERENCE

Serve any model behind one API.

140+ open and proprietary models, routed per request for quality, latency and cost. Swap models with a string.

LIVE ROUTING · LAST 24 H
MODEL
SHARE · P50
frontier-xl
62% · 412 ms
open-70b
26% · 188 ms
open-8b
10% · 64 ms
fallback
2% · n/a
QUALITY ≥ 0.92
41% LOWER COST
140+
models behind one endpoint
38 ms
median time to first token
11
regions with data residency

Four things you stop building yourself.

Routing, streaming, caching and regions ship with the API. There is no extra service to run.

Smart routing

Set a quality threshold once. Lattis picks the model per request and falls back automatically.

quality: 0.92 · fallback: 50 ms

Streaming everywhere

Text, audio and vision streams through one interface and one client.

stream: true · text · audio · vision

Caching

Semantic and exact caches cut repeat cost by up to 70%.

cache: semantic · hit rate 54%

Regions

11 regions, with data residency pinned per API key.

region: eu-central · pinned

Switch models with a string, not a migration.

Point the client at "auto" and set the bar. Pin a model when you need to, and change it later without touching the rest of your code.

Standard chat format, one client
Per-key spend limits and region pins
Every call traced with cost and latency
Python
TypeScript
cURL
chat.py
from lattis import Lattis
client = Lattis()
reply = client.chat(
model="auto",
quality=0.92,
messages=[{"role": "user", "content": prompt}],
)
print(reply.model, reply.cost)

Measured, not promised.

p50 across 1M production requests, September 2026. Methodology in the docs.

WORKLOAD
LATTIS
DIRECT PROVIDER
DIFFERENCE
Chat completion p50
Lattis
38 ms
Direct provider
61 ms
Difference
38% faster
Tool call round trip
Lattis
112 ms
Direct provider
190 ms
Difference
41% faster
Cold sandbox start
Lattis
0.9 s
Direct provider
4.2 s
Difference
4.6x faster
Cost per 1M tokens, routed
Lattis
$0.71
Direct provider
$1.20
Difference
41% lower
9x
41 ms
0
CUSTOMER STORY · PARCEL

“We did not add capacity. We added Lattis.”

Hannah Walsh
Engineering Manager, Parcel
Read the Parcel story

Inference, explained.

Still unsure? A solutions engineer can walk through your workload.

Which models are available?

140+ open and proprietary models across text, code, vision and audio. The catalogue updates every week.

Can I bring my own fine-tuned model?

Yes. Connect a fine-tune from a supported provider or upload your own weights. It gets the same endpoint, routing and traces as every other model.

How does routing decide?

Each request goes to the cheapest model that clears your quality threshold within your latency budget. Every decision is written to the trace.

What happens when a provider has an outage?

Requests fail over to an equivalent model in under 200 ms, with no code changes. The trace shows which model answered.

Start with 1M free tokens.

No card required. Production keys in two minutes.