Inference

Inference

Inference

Run open-weight models at scale - faster, cheaper, and without infrastructure headaches.

Run open-weight models at scale - faster, cheaper, and without infrastructure headaches.

Run open-weight models at scale - faster, cheaper, and without infrastructure headaches.

Build with the best open-weight models using kluster.ai’s high-speed, serverless inference layer. Whether you’re shipping chat apps, vision tools, coding copilots, or agentic workflows, you can run everything through a simple API call that scales as you grow.

Build with the best open-weight models using kluster.ai’s high-speed, serverless inference layer. Whether you’re shipping chat apps, vision tools, coding copilots, or agentic workflows, you can run everything through a simple API call that scales as you grow.

Build with the best open-weight models using kluster.ai’s high-speed, serverless inference layer. Whether you’re shipping chat apps, vision tools, coding copilots, or agentic workflows, you can run everything through a simple API call that scales as you grow.

Inference isn’t one size fits all.

Inference isn’t one size fits all.

Inference
isn’t one size fits all.

Real-time

Ultra-low-latency for live products, chatbots, and user-facing apps

Batch

Cost-effective for high-volume, asynchronous jobs and background processing

Powered by Adaptive Inference, our platform automatically adjusts for your workload, optimizing for throughput, accuracy, cost, and privacy.

Powered by Adaptive Inference, our platform automatically adjusts for your workload, optimizing for throughput, accuracy, cost, and privacy.

Powered by Adaptive Inference, our platform automatically adjusts for your workload, optimizing for throughput, accuracy, cost, and privacy.

Real-time

Batch

from openai import OpenAI
# OpenAI compatible API
client = OpenAI(
base_url="https://api.kluster.ai/v1",
api_key="my_klusterai_api_key"
)
response = client.chat.completions.create(
model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    messages=[
        {
            "role": "user",
            "content": "Provide an analysis of market trends in AI."
        }
    ]
)
print(response.choices[0].message.content)

Real-time

Batch

from openai import OpenAI
# OpenAI compatible API
client = OpenAI(
base_url="https://api.kluster.ai/v1",
api_key="my_klusterai_api_key"
)
response = client.chat.completions.create(
model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    messages=[
        {
            "role": "user",
            "content": "Provide an analysis of market trends in AI."
        }
    ]
)
print(response.choices[0].message.content)

Real-time

Batch

from openai import OpenAI
# OpenAI compatible API
client = OpenAI(
base_url="https://api.kluster.ai/v1",
api_key="my_klusterai_api_key"
)
response = client.chat.completions.create(
model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    messages=[
        {
            "role": "user",
            "content": "Provide an analysis of market trends in AI."
        }
    ]
)
print(response.choices[0].message.content)

Speed that scales

We’ve tuned our stack to be one of the fastest inference layers available today, often outperforming vLLM and vendor-native APIs. Cold starts are nearly eliminated, and you never wait on capacity.

Transparent pricing

Token-based pricing that scales with your usage, not your infrastructure bill.

Built for builders

Call any model with a few lines of code. All endpoints are OpenAI-compatible, so migrating is fast and painless.

Developer-first by design

-OpenAI compatible

endpoints

-Works with 

-Built-in support for RAG &

agents