LightweightReka

Reka Edge

Reka Edge is a lightweight multimodal AI model from Reka that processes text, images, and video with a 16K token context window for efficient inference.

Context 16K
Tier Lightweight
Modalities text, image, video
Input from
$0.100 / 1M tokens
across 1 provider

API Pricing

ProviderInput / 1MOutput / 1MUpdated
$0.100$0.1004/14/2026

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
Reka
Family
Reka
Tier
Lightweight
Context Window
16K
Modalities
Text, Image, Video

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

  • Supports three input modalities: text, images, and video
  • 16K token context window for processing substantial inputs
  • Lightweight architecture designed for efficient inference
  • Video processing capability uncommon in lightweight tier models
  • Multimodal reasoning across text and visual content
  • Optimized for speed and cost efficiency
  • No tool calling or function execution support
  • Proprietary model with weights not publicly available
  • Smaller context window compared to flagship models
  • Limited to inference tasks without agentic capabilities
  • Fewer overall capabilities than larger models in the Reka family

Key Features

16K token context window
Text input and generation
Image input processing
Video input processing
Multimodal content understanding
Streaming response support
Lightweight inference architecture

About Reka Edge

Reka Edge is Reka's lightweight multimodal AI model, positioned as the most efficient option in the Reka family. As a tier-optimized model, it's designed for scenarios where speed and cost efficiency take priority over maximum capability, while still maintaining multimodal functionality across text, images, and video inputs. The model operates with a 16,384 token context window and supports three input modalities: text, image, and video processing. This multimodal capability allows it to understand and reason about visual content alongside text, making it suitable for applications that need to process mixed media efficiently. However, it does not include tool calling or function execution capabilities, keeping the architecture focused on core inference tasks. Reka Edge targets use cases where organizations need multimodal AI capabilities but with faster response times and lower computational overhead than larger models. It competes in the lightweight category against other efficient multimodal models, offering video processing capabilities that are less common in this tier of models.

Common Use Cases

Reka Edge is well-suited for applications requiring efficient multimodal processing where cost and speed matter more than maximum capability. This includes content moderation systems that need to quickly analyze text, images, and video; automated media tagging and categorization; customer service bots that handle visual inquiries; and educational platforms that process mixed media content. Its video processing capability makes it particularly useful for social media platforms, security monitoring systems, and content analysis workflows that need to handle video inputs efficiently. The lightweight design makes it appropriate for high-volume deployments where processing many requests quickly is more important than handling the most complex reasoning tasks.

Frequently Asked Questions

How much does Reka Edge cost per million tokens?

Reka Edge pricing varies by provider and may include different rates for text versus image/video processing. Check the pricing table above for current rates across all available providers.

What is Reka Edge best used for?

Reka Edge excels at efficient multimodal processing tasks including content moderation, media analysis, automated tagging of images and videos, and customer support applications that need to handle visual content quickly. Its lightweight design makes it ideal for high-volume applications where speed and cost efficiency are priorities.

Can Reka Edge process video content?

Yes, Reka Edge supports video input processing alongside text and images, making it one of the few lightweight models with native video understanding capabilities. This allows it to analyze video content, extract information, and reason about temporal sequences in video data.