LightweightByteDance

Seed 2.0 Mini

Seed 2.0 Mini is ByteDance's lightweight multimodal model supporting text, image, and video inputs with a 262K token context window.

Context 262K
Tier Lightweight
Modalities text, image, video
Input from
$0.100 / 1M tokens
across 1 provider

API Pricing

ProviderInput / 1MOutput / 1MUpdated
$0.100$0.4004/14/2026

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

Model Details

General

Creator
ByteDance
Family
Seed
Tier
Lightweight
Context Window
262K
Modalities
Text, Image, Video

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

  • Supports video input processing in addition to text and images
  • Large 262K token context window for a lightweight model
  • Multimodal capabilities enable analysis of combined text and visual content
  • Lightweight tier offers cost-effective multimodal processing
  • Can process multiple media files in single requests due to large context window
  • Video sequence understanding capability
  • Developed by ByteDance with expertise in media processing
  • No tool calling or function execution capabilities
  • Proprietary model with no open source weights available
  • Lightweight tier may have reduced reasoning capabilities compared to flagship models
  • Limited to inference only without fine-tuning options

Key Features

262,144 token context window
Video input processing
Image input support
Text generation and analysis
Multimodal understanding across text, image, and video
Streaming response support
Batch processing capabilities
REST API access

About Seed 2.0 Mini

Seed 2.0 Mini is ByteDance's lightweight multimodal language model, part of the Seed family of models. As the compact tier offering in ByteDance's lineup, it provides multimodal capabilities at a reduced computational cost compared to larger models in the family. The model supports text, image, and video inputs with a substantial 262,144 token context window, allowing it to process lengthy documents or multiple media files in a single request. This multimodal capability enables it to analyze visual content, understand video sequences, and generate text responses based on combined text and visual inputs. However, it does not include tool calling functionality. Seed 2.0 Mini is designed for applications requiring multimodal understanding at scale, particularly where cost efficiency is important. Its video processing capabilities distinguish it from text-only lightweight models, making it suitable for content analysis, media understanding, and applications that need to process visual information alongside text.

Common Use Cases

Seed 2.0 Mini is well-suited for high-volume multimodal applications where cost efficiency is important. Its video processing capabilities make it ideal for content moderation, media analysis, video summarization, and automated content tagging. The large context window enables processing of long-form video content or multiple media files simultaneously. Use cases include social media content analysis, educational video processing, marketing asset evaluation, and automated video transcription with visual context. The lightweight nature makes it appropriate for applications requiring frequent multimodal inference calls where the full capabilities of flagship models are not necessary.

Frequently Asked Questions

How much does Seed 2.0 Mini cost per million tokens?

Seed 2.0 Mini pricing varies by provider and may have different rates for text versus image/video processing. Check the pricing table above for current rates across all providers.

What is Seed 2.0 Mini best used for?

Seed 2.0 Mini excels at cost-effective multimodal tasks, particularly video analysis, content moderation, media understanding, and applications requiring processing of combined text and visual inputs at scale.

Can Seed 2.0 Mini process long videos with its context window?

Yes, Seed 2.0 Mini's 262K token context window allows it to process substantial video content and multiple media files in a single request, making it suitable for analyzing longer video sequences or batch processing multiple media assets.