Best AI Inference Platforms in Asia

Integrate advanced AI capabilities into C# or VB.NET applications. LM-Kit.NET simplifies AI agent creation and deployment to enable intelligent, context-aware apps. LM-Kit.NET is designed for edge computing and leverages Small Language Models (SLMs), which are optimized to perform AI inference on the device. This approach reduces the dependency on remote servers and latency. It also ensures that data processing is secure and efficient, even in resource-constrained settings. LM-Kit.NET lets you experience the benefits of AI processing in real-time. Edge inference capabilities are available for both enterprise-grade software and agile prototypes. They deliver faster, more intelligent, and more reliable apps that keep up with today's dynamic digital environment.

Mistral AI is an advanced artificial intelligence company focused on open-source generative AI solutions. Offering adaptable, enterprise-level AI tools, the company enables deployment across cloud, on-premises, edge, and device-based environments. Key offerings include "Le Chat," a multilingual AI assistant designed for enhanced efficiency in both professional and personal settings, and "La Plateforme," a development platform for building and integrating AI-powered applications. With a strong emphasis on transparency and innovation, Mistral AI continues to drive progress in open-source AI and contribute to shaping AI policy.

Your software can see objects in video and images. A few dozen images can be used to train a computer vision model. This takes less than 24 hours. We support innovators just like you in applying computer vision. Upload files via API or manually, including images, annotations, videos, and audio. There are many annotation formats that we support and it is easy to add training data as you gather it. Roboflow Annotate was designed to make labeling quick and easy. Your team can quickly annotate hundreds upon images in a matter of minutes. You can assess the quality of your data and prepare them for training. Use transformation tools to create new training data. See what configurations result in better model performance. All your experiments can be managed from one central location. You can quickly annotate images right from your browser. Your model can be deployed to the cloud, the edge or the browser. Predict where you need them, in half the time.

OpenRouter provides a unified interface to LLMs. OpenRouter scouts for the lowest prices and best latencies/throughputs across dozens of providers, and lets you choose how to prioritize them. You don't need to change code when switching models or providers. You can even allow users to choose and pay for them. Evaluating models is flawed. Instead, compare them by how often they are used for different purposes. Chat with multiple people at once in a chatroom. Users, developers or both can pay for model usage. Model availability may change. APIs are also available to retrieve models, prices and limits. OpenRouter will route requests to the most suitable providers for your model based on your preferences. Requests are by default load-balanced to maximize uptime across the top providers, but you can customize this using the provider object within the request body. Prioritize providers who have not experienced significant outages within the last 10 seconds.

Vespa is forBig Data + AI, online. At any scale, with unbeatable performance. Vespa is a fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real-time. Users build recommendation applications on Vespa, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. To build production-worthy online applications that combine data and AI, you need more than point solutions: You need a platform that integrates data and compute to achieve true scalability and availability - and which does this without limiting your freedom to innovate. Only Vespa does this. Together with Vespa's proven scaling and high availability, this empowers you to create production-ready search applications at any scale and with any combination of features.

GMI GPU Cloud allows you to create generative AI applications within minutes. GMI Cloud offers more than just bare metal. Train, fine-tune and infer the latest models. Our clusters come preconfigured with popular ML frameworks and scalable GPU containers. Instantly access the latest GPUs to power your AI workloads. We can provide you with flexible GPUs on-demand or dedicated private cloud instances. Our turnkey Kubernetes solution maximizes GPU resources. Our advanced orchestration tools make it easy to allocate, deploy and monitor GPUs or other nodes. Create AI applications based on your data by customizing and serving models. GMI Cloud allows you to deploy any GPU workload quickly, so that you can focus on running your ML models and not managing infrastructure. Launch pre-configured environment and save time building container images, downloading models, installing software and configuring variables. You can also create your own Docker images to suit your needs.

Pipelines are permanent, models are temporary. Train, Evaluate, Deploy, Repeat. Valohai is the only MLOps platform to automate everything, from data extraction to model deployment. Automate everything, from data extraction to model installation. Automatically store every model, experiment, and artifact. Monitor and deploy models in a Kubernetes cluster. Just point to your code and hit "run". Valohai launches workers and runs your experiments. Then, Valohai shuts down the instances. You can create notebooks, scripts, or shared git projects using any language or framework. Our API allows you to expand endlessly. Track each experiment and trace back to the original training data. All data can be audited and shared.

Machine learning can do amazing things, including understanding the world, driving cars, writing code, and making art. It's still very difficult to use. Research is usually published in a PDF format. There are also bits of code on GitHub and weights (if you're fortunate!) on Google Drive. It's difficult to apply that work to a real-world problem unless you're an expert. Machine learning is now accessible to everyone. Machine learning models should be shared by people who create them. People who want to use machine-learning should not need a PhD to share their machine learning models. Great power comes with great responsibility. We believe that this technology can be made safer and more understandable by using better tools and safeguards.

Navigator provides rapid, location-independent answers to users, allowing them to create custom AI models that meet their individual needs. Experience innovation when technology complements human expertise. Create, manage, and watch content collaboratively with AI, co-workers and friends. Create custom AI models within minutes, not hours. Revitalize large models by streamlining training, reducing compute costs and incorporating attention steering. It seamlessly translates user interaction into manageable tasks. It chooses and executes AI models that are most appropriate for each task. The responses it delivers are in line with the user's expectations. No back doors, distributed storage and seamless inference. It uses distributed, edge-friendly technologies for lightning-fast interaction, wherever you are. Join our vibrant distributed storage eco-system to unlock access to the first watermarked universal models dataset.

Ollama is a cutting-edge platform that delivers AI-powered solutions tailored for users who want to seamlessly integrate machine learning into their projects. By offering a variety of tools for natural language processing and customizable AI capabilities, Ollama makes it easier for developers and organizations to enhance their applications with advanced AI functionalities, all while maintaining an intuitive user experience. Ollama allows users to run AI models locally as well.

Self-service machine learning platform that allows you to turn models into APIs with just a few mouse clicks. Sign up for a Deep Infra Account using GitHub, or login using GitHub. Choose from hundreds of popular ML models. Call your model using a simple REST API. Our serverless GPUs allow you to deploy models faster and cheaper than if you were to build the infrastructure yourself. Depending on the model, we have different pricing models. Some of our models have token-based pricing. The majority of models are charged by the time it takes to execute an inference. This pricing model allows you to only pay for the services you use. You can easily scale your business as your needs change. There are no upfront costs or long-term contracts. All models are optimized for low latency and inference performance on A100 GPUs. Our system will automatically scale up the model based on your requirements.

The complete LLM Platform with a superior developer's experience and robust infrastructure. Build, deploy and manage trusted, hyper-personalized and streamlined generative AI applications. Langbase is a new AI tool and inference engine for any LLM. It's an OpenAI alternative that's open-source. The most "developer friendly" LLM platform that can ship hyper-personalized AI applications in seconds.

Athina is a powerful AI development platform designed to help teams build, test, and monitor AI applications with ease. It provides robust tools for prompt management, evaluation, dataset handling, and observability, ensuring the creation of reliable and scalable AI solutions. With seamless integration capabilities for various AI models and services, Athina also prioritizes security with fine-grained access controls and self-hosted deployment options. As a SOC-2 Type 2 compliant platform, it offers a secure and collaborative environment for both technical and non-technical users. By streamlining workflows and enhancing team collaboration, Athina accelerates the development and deployment of AI-driven features.

NetApp AIPod is an advanced AI infrastructure solution designed to simplify the deployment and management of artificial intelligence workflows. Combining NVIDIA-validated systems like DGX BasePOD™ with NetApp’s cloud-connected all-flash storage, it offers a unified platform for analytics, training, and inference. This scalable solution enables organizations to accelerate AI adoption, streamline data workflows, and ensure seamless integration across hybrid cloud environments. With preconfigured, optimized infrastructure, AIPod reduces operational complexity and helps businesses gain insights faster while maintaining robust data security and management capabilities.

Machine learning models can be deployed at scale with greater accuracy. With more models in production, R&D can be turned into ROI. Seldon reduces time to value so models can get to work quicker. Scale with confidence and minimize risks through transparent model performance and interpretable results. Seldon Deploy cuts down on time to production by providing production-grade inference servers that are optimized for the popular ML framework and custom language wrappers to suit your use cases. Seldon Core Enterprise offers enterprise-level support and access to trusted, global-tested MLOps software. Seldon Core Enterprise is designed for organizations that require: - Coverage for any number of ML models, plus unlimited users Additional assurances for models involved in staging and production - You can be confident that their ML model deployments will be supported and protected.

Kubernetes is a highly scalable platform for model inference that uses standards-based models. Trusted AI. KServe, a Kubernetes standard model inference platform, is designed for highly scalable applications. Provides a standardized, performant inference protocol that works across all ML frameworks. Modern serverless inference workloads supported by autoscaling, including a scale up to zero on GPU. High scalability, density packing, intelligent routing with ModelMesh. Production ML serving is simple and pluggable. Pre/post-processing, monitoring and explainability are all possible. Advanced deployments using the canary rollout, experiments and ensembles as well as transformers. ModelMesh was designed for high-scale, high density, and often-changing model use cases. ModelMesh intelligently loads, unloads and transfers AI models to and fro memory. This allows for a smart trade-off between user responsiveness and computational footprint.

NVIDIA Triton™, an inference server, delivers fast and scalable AI production-ready. Open-source inference server software, Triton inference servers streamlines AI inference. It allows teams to deploy trained AI models from any framework (TensorFlow or NVIDIA TensorRT®, PyTorch or ONNX, XGBoost or Python, custom, and more on any GPU or CPU-based infrastructure (cloud or data center, edge, or edge). Triton supports concurrent models on GPUs to maximize throughput. It also supports x86 CPU-based inferencing and ARM CPUs. Triton is a tool that developers can use to deliver high-performance inference. It integrates with Kubernetes to orchestrate and scale, exports Prometheus metrics and supports live model updates. Triton helps standardize model deployment in production.

Towhee can automatically optimize your pipeline for production-ready environments by using our Python API. Towhee supports data conversion for almost 20 unstructured data types, including images, text, and 3D molecular structure. Our services include pipeline optimizations that cover everything from data decoding/encoding to model inference. This makes your pipeline execution 10x more efficient. Towhee integrates with your favorite libraries and tools, making it easy to develop. Towhee also includes a Python method-chaining API that allows you to describe custom data processing pipelines. Schemas are also supported, making it as simple as handling tabular data to process unstructured data.

Production-ready AI models that are fast and accurate. High-availability inference API that leverages the most advanced NVIDIA GPUs. We have selected the most popular open-source natural language processing models (NLP) and deployed them for the community. You can fine-tune your models (including GPT-J) or upload your custom models. Then, deploy them to production. Upload your AI models, including GPT-J, to your dashboard and immediately use them in production.

InferKit provides a web interface as well as an API to create AI-based text generators. There's something for everyone, whether you're an app developer or a novelist looking to find inspiration. InferKit's text generator takes the text you provide and generates what it thinks is next using a state of the art neural network. It can generate any length of text on virtually any topic and is configurable. You can use the tool via the web interface or through the developer API. Register now to get started. You can also use the network to write poetry or stories. Marketing and auto-completion are other possible uses. The generator can only understand a limited amount of text at once (currently, at most 3000 characters), so if you give it a longer prompt it will not use the beginning. The network is already trained and doesn't learn from inputs. Each request must contain at least 100 characters

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

We have the infrastructure to meet all your computing needs, whether you need one or thousands GPUs or one vCPU or tens of thousand vCPUs. Our resources are available whenever you need them. Our platform makes switching between GPU and CPU instances a breeze. You can easily deploy, modify and rescale instances to meet your needs. You can get outstanding machine learning performance without breaking your bank. The latest technology for a much lower price. Modern GPUs are built to meet your workload demands. Get access to computing resources that are tailored for your models. Our OblivusAI OS allows you to access libraries and leverage our infrastructure for large-scale inference. Use our robust infrastructure to unleash the full potential of gaming by playing games in settings of your choosing.

Fal is a serverless Python Runtime that allows you to scale your code on the cloud without any infrastructure management. Build real-time AI apps with lightning-fast inferences (under 120ms). You can start building AI applications with some of the models that are ready to use. They have simple API endpoints. Ship custom model endpoints that allow for fine-grained control of idle timeout, maximum concurrency and autoscaling. APIs are available for models like Stable Diffusion Background Removal ControlNet and more. These models will be kept warm for free. Join the discussion and help shape the future AI. Scale up to hundreds GPUs and down to zero GPUs when idle. Pay only for the seconds your code runs. You can use fal in any Python project simply by importing fal and wrapping functions with the decorator.

Fireworks works with the leading generative AI researchers in the world to provide the best models at the fastest speed. Independently benchmarked for the fastest inference providers. Use models curated by Fireworks, or our multi-modal and functionality-calling models that we have trained in-house. Fireworks is also the 2nd most popular open-source model provider, and generates more than 1M images/day. Fireworks' OpenAI-compatible interface makes it simple to get started. Dedicated deployments of your models will ensure uptime and performance. Fireworks is HIPAA-compliant and SOC2-compliant and offers secure VPC connectivity and VPN connectivity. Own your data and models. Fireworks hosts serverless models, so there's no need for hardware configuration or deployment. Fireworks.ai provides a lightning fast inference platform to help you serve generative AI model.

Lamini allows enterprises to transform proprietary data into next-generation LLM capabilities by offering a platform that allows in-house software teams the opportunity to upgrade to OpenAI level AI teams, and build within the security provided by their existing infrastructure. Optimised JSON decoding guarantees a structured output. Fine-tuning retrieval-augmented retrieval to improve photographic memory. Improve accuracy and reduce hallucinations. Inferences for large batches can be highly parallelized. Parameter-efficient finetuning for millions of production adapters. Lamini is the sole company that allows enterprise companies to develop and control LLMs safely and quickly from anywhere. It uses the latest research and technologies to create ChatGPT, which was developed from GPT-3. These include, for example, fine-tuning and RLHF.