Instantly run popular and specialized models, including Llama3, Mixtral, and Stable Diffusion, optimized for peak latency, throughput, and context length. FireAttention, our custom CUDA kernel, serves models four times faster than vLLM without compromising quality.
Meta Llama 3.1Mixtral MoE 8x22bStable Diffusion 3FireFunction V2Yi-LargeFireLlavaOpenAI WhisperGoogle Gemma 2Nomic EmbedFine-tune with our LoRA-based service, twice as cost-efficient as other providers. Instantly deploy and switch between up to 100 fine-tuned models to experiment without extra costs. Serve models at blazing-fast speeds of up to 300 tokens per second on our serverless inference platform.
Handle tasks with multiple models, modalities, and external APIs and data instead of relying on a single model. Use FireFunction, a SOTA function calling model, to compose compound AI systems for RAG, search, and domain-expert copilots for automation, code, math, medicine, and more.
FireFunctionFireworks Inference
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DatabaseInternetAPIsKnowledgeGraph"We've had a really great experience working with Fireworks to host open source models, including SDXL, Llama, and Mistral. After migrating one of our models, we noticed a 3x speedup in response time, which made our app feel much more responsive and boosted our engagement metrics."
Spencer Chan Product Lead - Poe by Quora
"Fireworks is the best platform out there to serve open source LLMs. We are glad to be partnering up to serve our domain foundation model series Ocean and thanks to its leading infrastructure we are able to serve thousands of LoRA adapters at scale in the most cost effective way."
Tim Shi CTO - Cresta
"Fireworks has been a fantastic partner in building AI dev tools at Sourcegraph. Their fast, reliable model inference lets us focus on fine-tuning, AI-powered code search, and deep code context, making Cody the best AI coding assistant. They are responsive and ship at an amazing pace."
Beyang Liu CTO - SourceGraph
We handle trillions of inferences daily, ensuring transparency, full model ownership, and complete data privacy—we don't store model inputs or outputs.
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