Off-peak computing Most affordable batch LLM Inference provider
50-90% cheaper than any other provider

Starting with Llama 3.1 70B & 8B

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-3.1-70b-Instruct FP16
($0.30/0.50 input/ouput per million tokens)

LIMITLESS
NO

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

Evaluation

LLM evaluation

E.g. Use Llama-3.1-70b
as a judge to evaluate the generation
performance in a RAG application
every night

Complex analysis

Contextual Retrieval

E.g. Use Llama-3.1-70b to generate a bit of context for each chunk
to improve the performance of RAG applications.

Classification

Classification

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

Translation

Translation

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

Parsing

Parsing

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

Synthesis

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-3.1-70b
instruct-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
llama-3.1-405b
instruct-fp16
128K tokens 24h Coming next
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.

1

Transparency

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

2

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.

3

Optimal use

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

4

Carbon credit

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

EXXA Key partners

partner 1
partner 2
partner 3
partner 4

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
EXXA API only supports llama-3.1-70b-instruct-fp16 for the moment. If you are interested in other language models or in other modalities, please contact us.
Output tokens
Models currently supported have a maximum output size of 4,098 tokens. 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 interface. 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.