Fireworks AI

Fireworks describes an unnamed global restaurant chain's audio intelligence pilot as live in 100 stores by March 2025 after a February proof of concept, with approximately 500ms transcription for real-time staff prompts.

Fireworks serves production customers including Cursor, Notion, Cresta, Vercel and Genspark; Notion reported latency reductions from about two seconds to 350 milliseconds.

Fireworks serves production customers including Cursor, Notion, Cresta, Vercel and Genspark; Notion reported latency reductions from about two seconds to 350 milliseconds.

Fireworks' July 10, 2026 MiniMax M3 kernel report documents a Blackwell SM100 KV-stationary sparse-attention path loading each selected KV block once and processing its assigned queries, with linked implementation repositories.

Fireworks combines inference optimization, speculative decoding, fine-tuning, reinforcement fine-tuning and elastic production inference, with customers using the platform for specialized production models and agent workloads.

Fireworks combines inference optimization, speculative decoding, fine-tuning, reinforcement fine-tuning and elastic production inference, with customers using the platform for specialized production models and agent workloads.

Fireworks announced on July 15, 2026 a US$1.505 billion Series D at a US$17.5 billion valuation, led by Atreides Management, Index Ventures and TCV.

Fireworks operates production inference and model-training infrastructure used by large AI applications and developer platforms, with evidence of enterprise-scale workloads across multiple customers.

Fireworks operates production inference and model-training infrastructure used by large AI applications and developer platforms, with evidence of enterprise-scale workloads across multiple customers.

Fireworks documents importing LoRA adapters trained on another platform for compatible tunable model architectures and preparing JSONL training/evaluation data. Adapter interchange and standard data workflows support transferable fine-tuning skills.

Fireworks roles and systems combine open-model serving, inference optimization, RL/RFT, developer infrastructure and production deployment, yielding broadly portable AI systems expertise.

Fireworks roles and systems combine open-model serving, inference optimization, RL/RFT, developer infrastructure and production deployment, yielding broadly portable AI systems expertise.