Skip to content

Prompt

Another question. I would like to begin using LLMs via API primarily as I scale up my production processes. I have a few questions and thoughts. The first is whether there exist any companies which kind of gather together a lot of LLM APIs so that I can try out different models without needing to maintain a lot of accounts. The second is whether there is an API that is particularly cost effective for running experiments with.

Output

Based on your questions and the information from the search results, I can provide you with some relevant answers and recommendations:

  1. Companies that aggregate LLM APIs:

Yes, there are companies that aggregate multiple LLM APIs, allowing you to access various models through a single interface. Some options include:

a) QuantILe AI:

  • Offers access and management of over 20+ LLM APIs through a single platform.
  • Provides features like call cascading, prompt adaptation, and cost management.
  • Currently in beta, but you can contact them for access.

b) Eden AI:

  • Offers a unified API to access multiple AI services, including LLMs.
  • Allows integration of various LLM tasks into cloud-based applications.
  • Provides access to multiple engines for optimizing cost and performance.

c) Monster API:

  • Offers a single API abstraction over numerous Generative AI models.
  • Provides no-code LLM fine-tuning, deployment, and scaling tools.

d) Pulze.ai:

  • Offers a single API that can route between different LLM providers.

  • Optimizes for maximum quality and minimal cost.

  • Cost-effective API for experiments:

For cost-effective experimentation, consider the following options:

a) Deepinfra:

  • Offers the lowest blended price at $0.36 per million tokens for Llama 3.1 70B.

b) Hyperbolic:

  • Second most cost-effective at $0.40 per million tokens for Llama 3.1 70B.

c) Together AI or Anyscale:

  • While not the cheapest, they offer straightforward setup processes and integration with LangChain, which could save you time and effort during experimentation.

d) Replicate:

  • Offers a simple one-line code implementation, making it easy to get started quickly for experiments.

For your use case of scaling up production processes and running experiments, I would recommend:

  1. Start with an aggregator like QuantILe AI or Eden AI. This will allow you to experiment with multiple LLMs without managing separate accounts and integrations.
  2. For cost-effective experimentation, consider using Deepinfra or Hyperbolic through these aggregators, if available. If not, you might want to set up direct access to these providers for your initial experiments.
  3. As you move towards production, you can then decide which specific LLMs or providers best suit your needs based on performance, cost, and integration capabilities.

Remember to always review the latest pricing and features, as the LLM landscape is rapidly evolving, and new, more cost-effective options may become available.

Extracted Prompts

Prompts/LLM API marketplace.md#Prompt 1