AI/LLM · Multi-Cloud

Reka AI

Reka trains and serves its own multimodal encoder–decoder frontier models (Core, Flash, Edge) on custom Kubernetes-based GPU clusters spanning multiple vendors, using PyTorch on large H100/A100 fleets and a separate A10/A100 inference stack.[2][5] Public deployment is via Reka’s own web app and API endpoints (chat.reka.ai, platform.reka.ai, showcase.reka.ai), with an OpenAI-compatible API server for Edge provided through vLLM and Hugging Face artifacts.[2][7][12]

Foundation proximity: Native (own / self-hosted weights)

Foundational models & how they consume them

PrimaryReka Core· Reka (self-hosted frontier model) · Native (own / self-hosted weights)

SecondaryReka Flash· Reka (self-hosted frontier model) · Native (own / self-hosted weights)

TertiaryReka Edge / reka-edge-2603· Reka (self-hosted frontier model; weights also published on Hugging Face) · Native (own / self-hosted weights)

Cloud & datastore

Multi-Cloud

Compliance

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Similar companies

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Head-to-head: Reka AI vs AI21 Labs Reka AI vs Aleph Alpha Reka AI vs Anthropic

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Explore

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FAQ

Does Reka AI use a foundational AI model?

Reka AI uses Reka Core, Reka Flash, Reka Edge / reka-edge-2603 (Native (own / self-hosted weights)).

What cloud does Reka AI run on?

Reka AI runs on Multi-Cloud.

How close does Reka AI run to the foundational model?

Reka AI is Native (own / self-hosted weights) — close to the metal, so cheaper tokens and more control over outputs.

Sources

reka.ai ↗

Also on the map

proprietary / self-built models

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