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Large scale inference at small scale cost

Large scale inference at small scale cost

Large scale inference at small scale cost

The developer platform that revolutionizes inference at scale

The developer platform that revolutionizes inference at scale

The developer platform that revolutionizes inference at scale

Built for developers by developers

Built for developers by developers

Built for developers by developers

We hate rate limits, too.

We hate rate limits, too.

We hate rate limits, too.

If you’re investing in a premium service, it should unlock faster growth for you, not slow you down with unexpected limits and hidden fees.

It’s time for a smarter solution.

If you’re investing in a premium service, it should unlock faster growth for you, not slow you down with unexpected limits and hidden fees.

It’s time for a smarter solution.

If you’re investing in a premium service, it should unlock faster growth for you, not slow you down with unexpected limits and hidden fees.

It’s time for a smarter solution.

Introducing
Adaptive Inference

Introducing
Adaptive Inference

Introducing
Adaptive Inference

Asynchronous inference with higher rate limits, predictable turnaround times, and unmatched value.

Asynchronous inference with higher rate limits, predictable turnaround times, and unmatched value.

Asynchronous inference with higher rate limits, predictable turnaround times, and unmatched value.

from openai import OpenAI
# OpenAI compatible API
client = OpenAI(base_url="https://api.kluster.ai/v1",
    api_key="your_klusterai_api_key", )
# Upload LLM requests
batch_input_file = client.files.create(
    file=open("batch_llm_requests.jsonl", "rb"), purpose="batch")
# Start adaptive inference
batch_request = client.batches.create(
    input_file_id=batch_input_file.id, endpoint="/v1/chat/completions",
    completion_window="24h")
# Wait for completion
while client.batches.retrieve(batch_request.id) != "completed":
    time.sleep(60)
# Download results
result_file_id = client.batches.retrieve(batch_request.id).output_file_id
llm_inference_results = client.files.content(result_file_id).content
from openai import OpenAI
# OpenAI compatible API
client = OpenAI(base_url="https://api.kluster.ai/v1",
    api_key="your_klusterai_api_key", )
# Upload LLM requests
batch_input_file = client.files.create(
    file=open("batch_llm_requests.jsonl", "rb"), purpose="batch")
# Start adaptive inference
batch_request = client.batches.create(
    input_file_id=batch_input_file.id, endpoint="/v1/chat/completions",
    completion_window="24h")
# Wait for completion
while client.batches.retrieve(batch_request.id) != "completed":
    time.sleep(60)
# Download results
result_file_id = client.batches.retrieve(batch_request.id).output_file_id
llm_inference_results = client.files.content(result_file_id).content

LLAMA 3.3, LLAMA 3.1 MODELS

LLAMA 3.3, LLAMA 3.1 MODELS

LLAMA 3.3, LLAMA 3.1 MODELS

Prices are million input/output tokens

Prices are million input/output tokens

Prices are million input/output tokens

Completion window time

MODEL SIZE

1 hour

3 hours

6 hours

12 hours

24 hours

8B

$.09

$.08

$.07

$.06

$.05

70B

$.35

$.33

$.30

$.25

$.20

405B

$1.75

$1.60

$1.45

$1.20

$.99

Completion window time

MODEL SIZE

1 hour

3 hours

6 hours

12 hours

24 hours

8B

$.09

$.08

$.07

$.06

$.05

70B

$.35

$.33

$.30

$.25

$.20

405B

$1.75

$1.60

$1.45

$1.20

$.99

Completion window time

MODEL SIZE

1 hour

3 hours

6 hours

12 hours

24 hours

8B

$.09

$.08

$.07

$.06

$.05

70B

$.35

$.33

$.30

$.25

$.20

405B

$1.75

$1.60

$1.45

$1.20

$.99

Why developers love kluster.ai

Why developers love kluster.ai

Why developers love kluster.ai

High volume by design

Experience seamless scalability and best-in-class rate limits, ensuring uninterrupted performance.

Predictable completion windows

Choose a timeframe that suits your needs—whether it’s an hour or a full day, we’ve got you covered.

Unmatched value


Achieve top-tier performance and reliability at half the cost of leading providers.

See what developers
have to say

See what developers
have to say

See what developers
have to say