EXXA - Most efficient batch API

Solution Key benefits

Off-Peak Computing is the most cost-efficient batch inference API for open-source models Get high quality output, at cheapest price, for all use cases when you can tolerate some delay!

ASYNCHRONOUS

24h

Get all your
requests under
than 24 hours.
Often much faster!

CHEAPEST

$0.34

Per million tokens
for Llama-3.3-70b-Instruct FP16
($0.30/0.50 input/ouput per million tokens)

LIMITLESS

Hard rate
limit

Solution How we do it?

Data centers have many short intervals of unused compute time—minutes or hours—that go to waste. Traditional systems cannot efficiently capture these brief windows, and once they are gone, the opportunity is lost.

At EXXA, we have created a custom scheduler and orchestrator that aggregates these unused fragments across multiple data centers, enabling us to run AI workloads efficiently on underutilized compute acquired at a discount.

We then pass those savings on to you.

Custom
scheduler

Maximize use of intermittent and low-costs compute with custom scheduler

Predictive inference
optimizer

Use optimal settings for each payload to process (incl. batch size, context size)

Specialized inference
engine

Custom inference engine optimized for batch API (incl. persistent KV cache, cross-platform and cross-GPU)

Self-training
draft model

Train smaller draft model on large batches to reduce workload of larger models and gain efficiencies

Solution Key use cases

LLM evaluation

E.g. Use most performing models
as a judge to evaluate the generation
of smaller models

Synthetic data

E.g. Use most performing models to generate large amount of synthetic data
to train new models

Classification

E.g. Classify large datasets
of documents, customer feedbacks
or news documents
on a daily basis

Translation

E.g. Translate large volume
of texts on multiple languages
using high performing models like llama-3-70B

Parsing

E.g. Extract data from large documents in a specific format. Use structured output feature on EXXA API.

Synthesis

E.g. Synthetize customers or internal chatbot conversations on a daily basis to reduce storage requirements.

Pricing Per-token rates

Base model	Context window	Delay	Input tokens	Prompt caching	Output tokens
llama-3.1-8b instruct-fp16	128K tokens	24h	$0.10 / M tokens	Write: $0.10 / M tokens Read: $0.02 / M tokens	$0.15 / M tokens
llama-3.3-70b instruct-fp16	128K tokens	24h	$0.30 / M tokens	Write: $0.30 / M tokens Read: $0.06 / M tokens	$0.50 / M tokens
deepseek-r1-distill llama-3.3-70b-fp16	128K tokens	24h	$0.30 / M tokens	Write: $0.30 / M tokens Read: $0.06 / M tokens	$0.50 / M tokens
llama-3.1-nemotron-70b instruct-fp16	128K tokens	24h	$0.30 / M tokens	Write: $0.30 / M tokens Read: $0.06 / M tokens	$0.50 / M tokens
beta:qwen-2-vl-72b instruct-fp16	32K tokens	24h	$0.30 / M tokens	Write: $0.30 / M tokens Read: $0.06 / M tokens	$0.50 / M tokens

Note: If you want access to other models, please contact us at founders@withexxa.com

EXXA Sustainability
commitments

The environmental footprint of Generative AI is substantial, with most recent projections showing up to 5x increase in digital CO2 emissions by 2030. At EXXA, we are dedicated to developing the most efficient LLM inference services while minimizing environmental impact. Our commitment to sustainability is built on the following four key principles.

Transparency

Measurement is the first step to any reduction. EXXA provides detailed energy consumption data for each request through our API.

Low-emissions GPUs

We prioritize the use of GPUs in regions with low-carbon electricity and schedule operations during off-peak hours to further reduce emissions when possible.

Optimal use

We maximize GPU efficiency through advanced technical solutions, aiming for the highest performance with the least environmental impact.

Carbon credit

We offer an easy option to offset any remaining carbon footprint by purchasing certified carbon credits directly through our platform.

Start using it today!

Get started

F.A.Q.

Use EXXA API ﹢

EXXA API is live and available. The Batch API endpoint, as documented here enables developers to submit request for asynchronous batch processing. Those requests will be processed under 24 hours.

Models supported ﹢

All models supported by EXXA API are listed here, including the beta version of Qwen-2-VL-72B. If you are interested in other models or in other modalities, please contact us.

Output tokens ﹢

The output size depends on the model. You can find the maximum output size for each model here. If you need higher output size please contact us.

Rate limits ﹢

There is no hard rate limit in terms of dataset size. However, you need to have enough credits on your account to launch the queries.

Pricing ﹢

When using EXXA off-peak API, you only pay for the input and output tokens. You can easily credit your account on the EXXA console. See Pricing section above for pricing details.

Countries supported ﹢

Payments are currently supported for the United States and France. More countries will follow. Contact us if your country is not listed and want access to the API.

Batch cancellation ﹢

It is possible to manually cancel any batch or request at any moment. If a batch is manually cancelled, any queries that have already been processed can be retrieved. Developers will be only charged for completed work.

Data retention ﹢

Data on EXXA API endpoint will be stored seven days after completion. EXXA is committed to privacy and trust for all our solutions. You own and control all the data shared to EXXA.

Private deployment ﹢

EXXA offers an entreprise solution to deploy such an LLM inference orchestrator on-premise or on Virtual Private Cloud. This is especially useful to maximize GPUs usage. Contact us to know more.

Off-peak computing Most affordable batch API