Anyscale Endpoints offers a fast, cost-effective, and scalable API service for developers to integrate leading open-source large language models like Llama 3 and Mixtral directly into any application.
Anyscale Endpoints is a fully managed API platform providing access to popular open-source large language models (LLMs). Built on the high-performance Ray framework, the service is engineered for enterprise-grade scalability, low latency, and high throughput. It targets developers and businesses who want to leverage the power of open-source AI without the significant overhead of hosting, managing, and scaling the inference infrastructure themselves. The core value proposition is its combination of performance and cost-effectiveness, offering pay-per-token pricing that is often much cheaper than proprietary model APIs. By providing an OpenAI-compatible API, it allows for a seamless transition for developers looking to experiment with or productionize open-source models like Llama 3 and Mixtral.
AI/ML engineers, application developers, and organizations of all sizes seeking to build applications with open-source LLMs without managing infrastructure. Ideal for those prioritizing performance, scalability, and cost-efficiency.
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2019
Berkeley, USA
Free Tier
New users receive $10 in free credits to use on any available model in Anyscale Endpoints.
Free
Pay-as-you-go
Users pay only for what they use based on the number of tokens processed. Pricing varies by model, for example: Llama-3-8B-Instruct is $0.15/1M tokens (input/output) and Mixtral-8x7B-Instruct is $0.50/1M tokens (input/output).
$0/mo
A direct competitor offering a similar cloud platform for running open-source AI models, often competing closely on price and model availability.
Users may choose OpenAI for exclusive access to their cutting-edge proprietary models like GPT-4o, though typically at a higher cost per token.
Another competitor focused on providing the fastest possible inference speeds for a variety of open-source and custom-trained models.
Developers choose self-hosting for maximum control, privacy, and customizability, but it requires significant operational effort and infrastructure management.
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