Run BiOS Adaptive — enterprise grade inference
One endpoint. Relevant responses, reduced AI spend.
BiOS Adaptive meets each request at the depth the task demands — simple prompts stay simple, hard problems get accurate, frontier-grade answers. One API call, and your AI spend can drop by more than half.
The problem
Most prompts are billed at rates they never needed
Everyone defaults to the strongest model for everything
It is the safe choice — and it means most prompts are billed at frontier rates they never needed.
One model cannot be right for every prompt
A classification call and a multi-step reasoning call have nothing in common. Paying frontier rates for both wastes money; paying budget rates for both wastes quality.
Providers go down
Hard-coding one model id into your product is a single point of failure you only discover during the outage.
How it works
One call in, the best-fit answer out
Your request arrives
The same OpenAI-compatible schema you already use. No SDK migration, no new client.
The task finds its depth
Each request is answered at the level the work demands — frontier strength when the prompt calls for it, budget speed when it does not.
The answer returns
Through the same endpoint you called. Failover is built in — an upstream hiccup never becomes your outage.
Who it is for
The same call, worth something different to each seat
For engineers
One integration, no babysitting. Point your existing OpenAI client at the endpoint and change nothing else — one id covers every task.
For product teams
A quality floor on hard prompts without frontier prices on easy ones. Simple prompts stay simple; hard prompts get strong, accurate answers — automatically.
For the business
You pay for what each answer took — the band below, with nothing stacked on top of it.
Pricing
The band is the savings mechanism, made visible
| Run BiOS Adaptive | Rate, per 1M tokens |
|---|---|
| Context window | 1M tokens |
| Input | $0.44 – $1.25 |
| Cached input | $0.14 |
| Output | $1.32 – $3.95 |
The rate varies because the work varies — and you only ever pay for what the answer took. A simple prompt bills at the bottom of the band; a demanding one bills at the top. Nothing is stacked on top of the rate itself.
The worst case is published, too. No request can bill above $1.25 input / $3.95 output per 1M tokens. Budget at the ceiling — every request that bills cheaper is savings you did not have to negotiate for.
USD per 1M tokens, as of 12 September 2026. Every request's rate is itemised on your invoice — you always see what the answer cost.
An honest fork
Pin a model, or let Adaptive meet each task
Pin a model when
- Your workload is uniform — every prompt costs the same decision.
- You are benchmarking or evaluating one specific model.
- A contract or budget needs one guaranteed per-token rate.
Use Adaptive when
- The workload is mixed — trivial prompts beside multi-step reasoning.
- The right price-quality trade-off differs request by request.
- You want failover built in, not bolted on.
Integration
Change two lines
OpenAI-compatible. Your existing client, your existing code.
from openai import OpenAI
client = OpenAI(
base_url="https://api.runbios.ai/v1", # was api.openai.com
api_key="sk-bios-...",
)
resp = client.chat.completions.create(
model="bios-adaptive", # was a pinned model id
messages=[{"role": "user", "content": "Classify this ticket"}],
)Prefer a pinned model? See models & pricing