Reka Core (and Reka Studio)

Reka Core is Reka AI’s top-tier multimodal large language model, built to handle complex reasoning across text, images, video, and audio. It sits at the center of the Reka platform and powers the Reka Studio web experience as well as enterprise deployments, enabling users to chat with documents, media, and tools in a single unified interface. Optimized for high‑stakes enterprise scenarios, Reka Core is positioned as the model you use when accuracy, reasoning depth, and cross‑modal understanding matter more than raw speed. Within Reka Studio, Reka Core can be applied to diverse data sources: uploaded documents and slide decks, image collections, video assets, and structured or semi‑structured knowledge bases. Paired with retrieval and grounding features, it can cite sources, follow chain‑of‑thought style reasoning internally, and produce structured outputs such as JSON that can be fed into downstream tools or pipelines. This makes it suitable for document review, investigative workflows, knowledge management, and analytics tasks that require both comprehension and synthesis over large, heterogeneous corpora. The model is exposed through the Reka API as well, alongside complementary models like Reka Flash and Reka Edge, so teams can pick the right tradeoff between speed, cost, and capability for each workload. Reka Core is described in Reka’s documentation as the superior, reasoning‑oriented option, designed for the most demanding applications, while lighter models are available for latency‑sensitive or on‑device scenarios. Reka also offers specialized services like Reka Vision and Reka Research that build on these base models to deliver turnkey video understanding and deep research workflows, giving organizations multiple entry points into the stack. What distinguishes Reka Core is its native multimodality and focus on enterprise deployments. Instead of bolting vision or audio on top of a text‑only LLM, the model is trained to understand and jointly reason over visual, auditory, and textual signals, which is critical in domains such as security, media, and defense where information rarely exists as plain text alone. Reka provides options for cloud API access, private or on‑premise deployments, and agentic platforms that can orchestrate tools and browse the web or private repositories, allowing enterprises to embed Reka Core into secure, custom workflows that respect data governance requirements.

• ✓Analyze thousands of internal PDF reports and slide decks to generate consolidated executive summaries with cited sources.
• ✓Build an internal knowledge assistant that answers employee questions over wikis, tickets, and policy documents using grounded retrieval.
• ✓Review and annotate security or compliance incidents by jointly analyzing log text, screenshots, and short video clips.
• ✓Power an AI copilot inside a CRM or ticketing system that drafts responses and action plans using customer history and attached files.
• ✓Drive an agentic workflow that orchestrates APIs and tools to research a topic, read attached documents, and return a structured recommendation report.

Start in Reka Studio, select Reka Core as the underlying model, and clearly describe your task and data context in the system or initial prompt, specifying the desired output format (for example, JSON with defined keys) to get structured results. For document or media analysis, upload files first, verify they are indexed or attached to the session, then ask targeted questions that reference the corpus explicitly, such as “Using only the uploaded contracts, summarize term changes by counterparty.” When building agents or connecting to external tools via API, design prompts that spell out tool usage rules and constraints, and test with small, representative examples before scaling. For API use, monitor token usage and latency, set sensible max token and temperature parameters for your workload, and log both prompts and outputs so you can iteratively refine instructions and catch edge cases.

Pricing and quota details for Reka Core and Reka Studio are not clearly exposed on the public marketing site, so teams may need to contact sales or rely on dashboard information for exact costs and limits. As with other large multimodal models, Reka Core can hallucinate plausible but incorrect statements, especially when asked about facts not grounded in provided context, and may misinterpret low‑quality or ambiguous visual or audio inputs. The platform is primarily oriented toward technical and enterprise users, so effective use of the API and agentic workflows requires familiarity with prompt design and integration patterns. Some advanced deployment options, such as private or on‑premise hosting and SSO, appear to be gated behind enterprise agreements, which can add lead time for smaller teams.