Compare the Top LLM API Providers that integrate with DeepSeek R1 as of October 2025

This a list of LLM API providers that integrate with DeepSeek R1. Use the filters on the left to add additional filters for products that have integrations with DeepSeek R1. View the products that work with DeepSeek R1 in the table below.

What are LLM API Providers for DeepSeek R1?

LLM API providers offer developers and businesses access to sophisticated language models and LLM APIs via cloud-based interfaces, enabling applications such as chatbots, content generation, and data analysis. These APIs abstract the complexities of model training and infrastructure management, allowing users to integrate advanced language understanding into their systems seamlessly. Providers typically offer a range of models optimized for various tasks, from general-purpose language understanding to specialized applications like coding assistance or multilingual support. Pricing models vary, with some providers offering pay-as-you-go plans, while others may have subscription-based pricing or free tiers for limited usage. The choice of an LLM API provider depends on factors such as model performance, cost, scalability, and specific use case requirements. Compare and read user reviews of the best LLM API providers for DeepSeek R1 currently available using the table below. This list is updated regularly.

  • 1
    Amazon Bedrock
    Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices.
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  • 2
    Vertex AI
    Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.
    Starting Price: Free ($300 in free credits)
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  • 3
    RunPod

    RunPod

    RunPod

    RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.
    Starting Price: $0.40 per hour
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  • 4
    Snowflake

    Snowflake

    Snowflake

    Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.
    Starting Price: $2 compute/month
  • 5
    DeepSeek

    DeepSeek

    DeepSeek

    DeepSeek is a cutting-edge AI assistant powered by the advanced DeepSeek-V3 model, featuring over 600 billion parameters for exceptional performance. Designed to compete with top global AI systems, it offers fast responses and a wide range of features to make everyday tasks easier and more efficient. Available across multiple platforms, including iOS, Android, and the web, DeepSeek ensures accessibility for users everywhere. The app supports multiple languages and has been continually updated to improve functionality, add new language options, and resolve issues. With its seamless performance and versatility, DeepSeek has garnered positive feedback from users worldwide.
    Starting Price: Free
  • 6
    Snowflake Cortex AI
    Snowflake Cortex AI is a fully managed, serverless platform that enables organizations to analyze unstructured data and build generative AI applications within the Snowflake ecosystem. It offers access to industry-leading large language models (LLMs) such as Meta's Llama 3 and 4, Mistral, and Reka-Core, facilitating tasks like text summarization, sentiment analysis, translation, and question answering. Cortex AI supports Retrieval-Augmented Generation (RAG) and text-to-SQL functionalities, allowing users to query structured and unstructured data seamlessly. Key features include Cortex Analyst, which enables business users to interact with data using natural language; Cortex Search, a hybrid vector and keyword search engine for document retrieval; and Cortex Fine-Tuning, which allows customization of LLMs for specific use cases.
    Starting Price: $2 per month
  • 7
    Parasail

    Parasail

    Parasail

    Parasail is an AI deployment network offering scalable, cost-efficient access to high-performance GPUs for AI workloads. It provides three primary services, serverless endpoints for real-time inference, Dedicated instances for private model deployments, and Batch processing for large-scale tasks. Users can deploy open source models like DeepSeek R1, LLaMA, and Qwen, or bring their own, with the platform's permutation engine matching workloads to optimal hardware, including NVIDIA's H100, H200, A100, and 4090 GPUs. Parasail emphasizes rapid deployment, with the ability to scale from a single GPU to clusters within minutes, and offers significant cost savings, claiming up to 30x cheaper compute compared to legacy cloud providers. It supports day-zero availability for new models and provides a self-service interface without long-term contracts or vendor lock-in.
    Starting Price: $0.80 per million tokens
  • 8
    kluster.ai

    kluster.ai

    kluster.ai

    Kluster.ai is a developer-centric AI cloud platform designed to deploy, scale, and fine-tune large language models (LLMs) with speed and efficiency. Built for developers by developers, it offers Adaptive Inference, a flexible and scalable service that adjusts seamlessly to workload demands, ensuring high-performance processing and consistent turnaround times. Adaptive Inference provides three distinct processing options: real-time inference for ultra-low latency needs, asynchronous inference for cost-effective handling of flexible timing tasks, and batch inference for efficient processing of high-volume, bulk tasks. It supports a range of open-weight, cutting-edge multimodal models for chat, vision, code, and more, including Meta's Llama 4 Maverick and Scout, Qwen3-235B-A22B, DeepSeek-R1, and Gemma 3 . Kluster.ai's OpenAI-compatible API allows developers to integrate these models into their applications seamlessly.
    Starting Price: $0.15per input
  • 9
    SambaNova

    SambaNova

    SambaNova Systems

    SambaNova is the leading purpose-built AI system for generative and agentic AI implementations, from chips to models, that gives enterprises full control over their model and private data. We take the best models, optimize them for fast tokens and higher batch sizes, the largest inputs and enable customizations to deliver value with simplicity. The full suite includes the SambaNova DataScale system, the SambaStudio software, and the innovative SambaNova Composition of Experts (CoE) model architecture. These components combine into a powerful platform that delivers unparalleled performance, ease of use, accuracy, data privacy, and the ability to power every use case across the world's largest organizations. We give our customers the optionality to experience through the cloud or on-premise.
  • 10
    Groq

    Groq

    Groq

    Groq is on a mission to set the standard for GenAI inference speed, helping real-time AI applications come to life today. An LPU inference engine, with LPU standing for Language Processing Unit, is a new type of end-to-end processing unit system that provides the fastest inference for computationally intensive applications with a sequential component, such as AI language applications (LLMs). The LPU is designed to overcome the two LLM bottlenecks, compute density and memory bandwidth. An LPU has greater computing capacity than a GPU and CPU in regards to LLMs. This reduces the amount of time per word calculated, allowing sequences of text to be generated much faster. Additionally, eliminating external memory bottlenecks enables the LPU inference engine to deliver orders of magnitude better performance on LLMs compared to GPUs. Groq supports standard machine learning frameworks such as PyTorch, TensorFlow, and ONNX for inference.
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