LLM Reference

Reka Core

Released
2024-04-15
Last refreshed
2026-07-10
Status
Researched 251d ago
ProprietaryCommercial use: conditionalMultimodalRAGAgentsLong contextVisionJSON / Tool use

Reka Core is worth evaluating for rag, agents, and long context when its provider route and context window match the workload.

Use it for

  • Teams evaluating rag, agents, and long context
  • Workloads that can use a 128k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Workloads where another current model has stronger sourced task evidence
Specifications
Family
Reka
Released
2024-04-15
Context
128k
Architecture
Decoder Only
Knowledge cutoff
2023-11
Specialization
general
Openness
Proprietary
License
ProprietaryCommercial use: conditional
Weights
Not released
Code
Unknown
Training
Fine-tuned
Created by
RekaReka

Developing customizable generative AI models for enterprises.

Palo Alto, California, United States
Founded 2023
Website
Pricing
Output / 1M
$6.00
Input / 1M
$2.00

Cheapest of 1 route · Reka Platform

Providers(1)
Reka Platform
View 1 provider route

About

Reka's frontier-class multimodal model for complex tasks. Approaches OpenAI/Google/Anthropic frontier models

Top use-case fit: coding, agents, and build tasks

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Reka Platform$2.00$6.00
Serverless

Capabilities

MultimodalJSON / Tool use

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

API versions

reka-core-20240415reka-core-20240501