On-Demand Language Models

Dedicated Inference, Instantly Ready to Handle Massive Workloads.

Model Title

Reference to HF

0
1
2

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Size: 50B

Bits: 16b

Max. Context: 10k

Model Title

Reference to HF

0
1
2

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum.

Size: 50B

Bits: 16b

Max. Context: 10k

More Models

No Rate Limits, No Delays

Launch Your Own Dedicated Model Instantly – Built for Big Data.

20x faster boot

Using Instant Provisioning.

10k tokens/s

Throughput for models sized up to 14B parameters.

5x cheaper

Comparing open-source to closed-source models such as GPT-4o.

Instantly Production-Ready

Launch effortlessly with a few lines of code—leave infrastructure to us.

from cortecs_py.client import Cortecs
from cortecs_py.integrations import DedicatedLLM

cortecs = Cortecs()

with DedicatedLLM(cortecs, model_name='<MODEL_NAME>') as llm:
    essay = llm.invoke('Write an essay about LLMs')
    print(essay.content)

Drop-in replacement.

All Models come with an OpenAI-compatible endpoint, allowing you to use popular tools like LangChain or CrewAI right away.

Dynamic provisioning.

Dynamic provisioning allows LLMs to be allocated automatically when and where needed, optimizing costs.

Security First.

Secure solutions designed to meet strict standards.

  • GDPR compliant

  • ISO certified hosting

  • TLS encryption

Maximum Privacy

Data remains entirely owned by the user, with no sharing, storage, or use for training purposes. All data transferred is TLS-encrypted.

EU Standards

The compute infrastructure is operated and maintained within the EU. All compute is ISO-27001 certified and strictly adheres to GDPR regulations.

Frequently Asked Questions

When to choose On-Demand Inference?

On-demand inference is a good choice when applications need reliable, low-latency performance or handle heavy or batch workloads. With dedicated inference, you have exclusive access to a model and its compute resources, so performance remains consistent without competing traffic from other users. This setup is especially effective for tasks that can’t afford delays and need steady resource availability.

Can I use my own model?

Yes we do support custom deployments. Therefore get in touch with our experts.

Is my data stored or used for training?

No, none of your data is stored or used for training.

What's Instant Provisioning?

Instant provisioning allows the access to dedicated language models without the usual setup delays. Instead of dealing with extensive configurations, users gain immediate access to a private LLM endpoint. This setup means that even large models, with many billions of parameters, are instantly available on demand.

Instant provisioning suits batch and scheduled jobs by allowing models to be spun up only when needed, optimizing both resource use and costs. This flexible, on-demand approach minimizes idle time and eliminates operational overhead.

Contact Us

Contact us via email. Additionally, our discord server is accessible to developers.

Enterprise

Prefer to run your own fine-tuned model? Connect with our experts for tailored LLM-Inference solutions.

Support

Reach out to customer support for assistance with general inquiries or specific concerns.