Fireworks AI - Enterprise-grade AI model deployment and scaling platform

Fireworks AI Enterprise-grade AI model deployment and scaling platform

What is Fireworks AI?

Fireworks AI provides a comprehensive platform for deploying and scaling AI models, offering serverless inference capabilities across text, image, and multi-modal applications. The platform supports a wide range of model deployments, from small-scale projects to enterprise-level implementations, with flexible GPU allocation and high-performance computing resources.

The service features advanced capabilities including speech-to-text processing, embedding models, and fine-tuning options, all backed by cutting-edge infrastructure utilizing A100, H100, and H200 GPUs. With support for team collaboration and up to 100 deployed models in the developer tier, Fireworks AI ensures reliable and scalable AI model deployment.

Features

Serverless Inference: Support for up to 6,000 RPM and 2.5 billion tokens/day
Multi-modal Support: Text, image, and vision model deployment capabilities
Flexible Deployment: Up to 16 GPUs on-demand with no rate limits
Fine-tuning Services: Custom model training with various parameter sizes
Enterprise Scaling: Dedicated and self-hosted deployment options

Use Cases

Large-scale text generation and processing
Enterprise AI model deployment
Custom model fine-tuning and training
Image generation and processing
Speech-to-text transcription
Multi-modal AI applications

FAQs

How is serverless text model pricing calculated?

Pricing is based on the base model parameter count, ranging from $0.10 to $8.00 per 1M tokens, applying to both input and output tokens.
What are the available GPU types for on-demand deployment?

Available GPU types include A100 80GB ($2.90/hour), H100 80GB ($5.80/hour), H200 141GB ($9.99/hour), and AMD MI300X ($4.99/hour).
How does the spending limit system work?

Spending limits are determined by total historical Fireworks spend, with tiers ranging from $50/month to $50,000/month based on qualification criteria.