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What is Nextbit Inference?

Nextbit Inference delivers open-weight AI models through API endpoints that match the request formats used by both OpenAI and Anthropic. Developers can explore an extensive catalog of models and conveniently utilize them via standard client libraries, all governed by a token-based pricing system. The platform offers both shared serverless inference and dedicated single-tenant endpoints that ensure consistent capacity. Moreover, Nextbit supports model fine-tuning and provides deployment services for custom and fine-tuned models alike. This platform is tailored for AI and machine-learning engineers who are dedicated to creating applications, agents, and efficient workflows for production inference. Clients can choose between EU or global endpoints, with dedicated deployments customizable to align with specific data-location and infrastructure needs. The API is crafted for easy integration into current development practices, while the serverless inference option allows users to harness GPU-backed model serving without the hassle of managing the underlying infrastructure. This all-encompassing service not only streamlines the development process but also enables developers to stay agile and innovative in the rapidly changing AI sector, fostering the creation of cutting-edge solutions and applications.

What is KServe?

KServe stands out as a powerful model inference platform designed for Kubernetes, prioritizing extensive scalability and compliance with industry standards, which makes it particularly suited for reliable AI applications. This platform is specifically crafted for environments that demand high levels of scalability and offers a uniform and effective inference protocol that works seamlessly with multiple machine learning frameworks. It accommodates modern serverless inference tasks, featuring autoscaling capabilities that can even reduce to zero usage when GPU resources are inactive. Through its cutting-edge ModelMesh architecture, KServe guarantees remarkable scalability, efficient density packing, and intelligent routing functionalities. The platform also provides easy and modular deployment options for machine learning in production settings, covering areas such as prediction, pre/post-processing, monitoring, and explainability. In addition, it supports sophisticated deployment techniques such as canary rollouts, experimentation, ensembles, and transformers. ModelMesh is integral to the system, as it dynamically regulates the loading and unloading of AI models from memory, thus maintaining a balance between user interaction and resource utilization. This adaptability empowers organizations to refine their ML serving strategies to effectively respond to evolving requirements, ensuring that they can meet both current and future challenges in AI deployment.

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Integrations Supported

Amazon Web Services (AWS)
Anthropic
Claude Code
Cline
Cursor
Datadog
Google Cloud Platform
Microsoft Azure
OpenAI

Integrations Supported

Bloomberg
Docker
Gojek
IBM Cloud
Kubeflow
NAVER
NVIDIA DRIVE
ZenML
Zillow
vLLM

API Availability

Has API

API Availability

Has API

Pricing Information

$0.075/1M input tokens
Serverless inference is billed per million input and output tokens at model-specific rates; Gemma 3 12B starts at $0.075 per million input tokens and $0.15 per million output tokens. Dedicated Inference uses a fixed monthly fee paid upfront, with 6-, 12-, 18-, or 24-month commitments and capacity-based tiers.

Pricing Information

Free
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

NEXTBIT 256, S.L.

Date Founded

2021

Company Location

Spain

Company Website

www.nextbit256.com

Company Facts

Organization Name

KServe

Company Website

kserve.github.io/website/latest/

Categories and Features

AI Inference

Not specified

LLM API

Not specified

Categories and Features

AI Inference

Not specified

Machine Learning

Not specified

ML Model Deployment

Not specified

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