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Fireworks AI provides fast and cost-effective inference for open-weight models with a focus on production-grade reliability.
6
indexed models
6
total catalog
$3.000
cheapest model
0
free / open source
| Model | Input $/1M | Output $/1M | Context | |
|---|---|---|---|---|
Fireworks: Ember-1 Ember-1 is a specialized reasoning model from Fireworks Research, built on [Kimi K3](https://openrouter.ai/moonshotai/kimi-k3). It is designed to make every token go further: it produces shorter reasoning traces, using roughly 40%... | $3.000 | $15.000 | 1.048576M | |
flux-kontext-max I don't have reliable information about a model called "flux-kontext-max" by Fireworks in my training data, so I cannot provide a factual description of it. I'd recommend checking Fireworks' official documentation or website for accurate details about this model's capabilities and intended users. | — | — | — | |
flux-1-dev-fp8 A quantized version of Flux 1 Dev optimized for faster inference and lower memory requirements, ideal for developers and organizations seeking to generate high-quality images with reduced computational costs. |
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flux-kontext-pro I don't have reliable information about a model called "flux-kontext-pro" by Fireworks in my training data, so I cannot provide an accurate description of its capabilities and intended users. | — | — | — |
glm-5 A high-capacity language model with 203K token context window designed for processing long documents, complex reasoning tasks, and detailed analysis, ideal for researchers, developers, and enterprises requiring extended context understanding without frequent summarization. | — | — | 203k |
glm-5p1 This long-context language model excels at processing and analyzing documents up to 203K tokens, making it ideal for researchers, analysts, and developers who need to work with extensive codebases, legal documents, or comprehensive datasets in a single request. | — | — | 203k |