LightweightByteDance

Seed 2.0 Lite

Seed 2.0 Lite 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
$0.250 / 1M tokens
across 1 provider
Compare Prices

API Pricing

ProviderInput / 1MOutput / 1MUpdated
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OpenRouter
$0.250$2.004/14/2026

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
Aliases
seed-2-0-lite

Strengths & Limitations

  • Supports three modalities: text, image, and video input
  • Large 262K token context window for extended content processing
  • Lightweight architecture optimized for efficiency
  • Native video understanding capabilities
  • Part of ByteDance's established Seed model family
  • Suitable for high-throughput multimodal applications
  • Lower computational requirements than full-size multimodal models
  • No tool calling or function execution support
  • Proprietary model with no open-source availability
  • Lightweight tier may have reduced capabilities compared to flagship multimodal models
  • Limited to ByteDance's API ecosystem
  • May have constraints on video processing length or resolution

Key Features

•262K token context window
•Text input and generation
•Image input processing
•Video input understanding
•Multimodal content analysis
•Cross-modal reasoning capabilities
•Lightweight model architecture
•Streaming response support

About Seed 2.0 Lite

Seed 2.0 Lite is ByteDance's lightweight multimodal model within the Seed family, designed for efficient processing across text, image, and video modalities. As the lite variant, it offers a balance between capability and computational efficiency compared to larger models in the family. The model features a 262,144 token context window and native support for text, image, and video inputs, enabling multimodal understanding and generation tasks. This combination of modalities allows it to process and analyze visual content alongside textual information, making it suitable for applications requiring cross-modal reasoning. Seed 2.0 Lite targets use cases where multimodal capabilities are needed but computational resources or latency requirements favor a more efficient model. It competes with other lightweight multimodal models in scenarios requiring video understanding, visual question answering, and content analysis across multiple input types.

Common Use Cases

Seed 2.0 Lite is well-suited for applications requiring efficient multimodal processing, particularly where video understanding is important. Its lightweight design makes it appropriate for content moderation systems that need to analyze text, images, and videos at scale. The model works well for educational platforms requiring multimedia content analysis, social media applications needing cross-modal content understanding, and customer service systems that handle diverse input types. The large context window enables processing of longer video content or multiple media files in a single request, while the efficient architecture supports high-throughput scenarios where cost and latency matter more than maximum capability.

Frequently Asked Questions

How much does Seed 2.0 Lite cost per million tokens?

Seed 2.0 Lite pricing varies by provider and usage type. Check the pricing table above for current rates across all available providers.

What is Seed 2.0 Lite best used for?

Seed 2.0 Lite excels at multimodal tasks requiring text, image, and video understanding where efficiency is important. It's well-suited for content moderation, educational content analysis, social media processing, and applications needing video understanding capabilities with lower computational overhead than flagship multimodal models.

Does Seed 2.0 Lite support tool calling or function execution?

No, Seed 2.0 Lite does not support tool calling or function execution capabilities. It focuses on multimodal understanding and generation across text, image, and video inputs without external tool integration.