Fireworks AI
Fastest Inference for Generative AI
Fireworks AI is a ai tools tool built by Fireworks AI, Inc.. It's best for AI developers and Startups building AI applications. Pricing is usage based. Main alternatives include env zero, Docker, Turso.
Pricing
usage based
Audience
AI developers
Platforms
Community
0%
About Fireworks AI
Fireworks AI provides a platform for building, tuning, and scaling generative AI models. It offers fast inference speeds, optimized open-source models, and complete AI model lifecycle management.
Fireworks AI is a cloud platform designed to accelerate the development and deployment of generative AI applications. It provides access to state-of-the-art, open-source LLMs and image models, optimized for speed, cost, and quality. The platform allows users to run models with a single line of code, fine-tune them using advanced techniques, and scale production workloads seamlessly.
Key features include a globally distributed virtual cloud infrastructure, enterprise-grade security, and a fast inference engine. Fireworks AI supports various use cases, such as code assistance, conversational AI, agentic systems, search, and multimodal applications. It offers complete AI model lifecycle management, from experimentation to production, without the need for infrastructure management.
The platform caters to both AI natives and enterprises, offering day-0 support for the latest models, high-quality performance at a low cost, and a comprehensive set of developer features. For enterprises, Fireworks AI provides SOC2, HIPAA, and GDPR compliance, along with options to bring their own cloud or run on Fireworks' infrastructure with zero data retention and complete data sovereignty.
Fireworks AI differentiates itself by providing a serverless inference model, fine-tuning capabilities, and on-demand deployments. This allows users to start building in seconds, customize open models with their own data, and pay per GPU second for faster speeds and higher rate limits at scale.
Fireworks AI targets AI developers, startups, and enterprises looking to build and deploy generative AI applications quickly and efficiently. It is particularly well-suited for those who want to leverage open-source models without the complexity of managing infrastructure.
Key Features
Pricing
usage basedFireworks AI offers serverless pricing based on per-token usage, with different rates for various models and parameter sizes. They also offer fine-tuning pricing per 1M training tokens and on-demand pricing per GPU second. They provide $1 in free credits to get started.
Serverless Pricing (Text and Vision):
* Less than 4B parameters: $0.10 / 1M tokens
* 4B - 16B parameters: $0.20 / 1M tokens
* More than 16B parameters: $0.90 / 1M tokens
* MoE 0B - 56B parameters (e.g. Mixtral 8x7B): $0.50 / 1M tokens
* MoE 56.1B - 176B parameters (e.g. DBRX, Mixtral 8x22B): $1.20 / 1M tokens
* DeepSeek V3 family: $0.56 input, $1.68 output
* GLM-4.7: $0.60 input, $2.20 output
* GLM-5: $1.00 input, $0.20 cached input, $3.20 output
* GLM-5.1: $1.40 input, $0.26 cached input, $4.40 output
* Qwen3 VL 30B A3B: $0.15 input, $0.60 output
* Kimi K2 Instruct, Kimi K2 Thinking: $0.60 input, $2.50 output
* Kimi K2.5: $0.60 input, $0.10 cached input, $3.00 output
* Kimi K2.5 Turbo: $0.99 input, $0.16 cached input, $4.94 output
* OpenAI gpt-oss-120b: $0.15 input, $0.60 output
* OpenAI gpt-oss-20b: $0.07 input, $0.30 output
* MiniMax 2.5: $0.30 input, $0.03 cached input, $1.20 output
* MiniMax 2.7: $0.30 input, $0.06 cached input, $1.20 output
Speech to Text (STT):
* Whisper-v3-large: $0.0015 / audio minute
* Whisper-v3-large-turbo: $0.0009 / audio minute
Image Generation:
* All Non-Flux Models (SDXL, Playground, etc): $0.00013 per step ($0.0039 per 30 step image)
* FLUX.1 [dev]: $0.0005 per step ($0.014 per 28 step image)
* FLUX.1 [schnell]: $0.00035 per step ($0.0014 per 4 step image)
* FLUX.1 Kontext Pro: $0.04 per image
* FLUX.1 Kontext Max: $0.08 per image
Embeddings:
* up to 150M: $0.008 / 1M input tokens
* 150M - 350M: $0.016 / 1M input tokens
* Qwen3 8B: $0.1 / 1M input tokens
Fine Tuning Pricing (per 1M training tokens):
* Models up to 16B parameters:
* LoRA SFT: $0.50
* LoRA DPO: $1.00
Who is it for?
Best for
- Rapid prototyping of AI applications
- Scaling AI production workloads
- Fine-tuning open-source models
- Building AI-powered code assistants
- Creating conversational AI applications
- Developing agentic systems
- Implementing AI-enhanced search
- Building multimodal applications
Not ideal for
- Organizations requiring complete control over infrastructure
- Use cases with extremely strict data residency requirements (unless BYOC is used)
- Projects with very limited budgets (free credits are available, but usage-based pricing applies)
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