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Seed-2.0-Mini

Seed-2.0-Mini is a compact multimodal large language model from ByteDance Seed optimized for latency-sensitive, high-concurrency, and cost-sensitive applications, offering long context and flexible reasoning modes.

Start Using API

What is Seed-2.0-Mini?

Seed-2.0-Mini is a proprietary ByteDance Seed model that accepts text, image, and video inputs and produces text outputs with a context window of roughly 256k tokens. It is mainly used for fast, cost-efficient text generation, chat, and lightweight reasoning workloads where rapid response and high throughput are important. It is also used for multimodal understanding tasks—such as interpreting images or video alongside text—and for tool use, structured outputs, and extended reasoning within long documents. Seed-2.0-Mini belongs to the Doubao/Seed 2.0 model family and offers performance comparable to ByteDance Seed 1.6 while emphasizing lower latency and cost.

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).

Provider Input Output Cache read /M Latency Throughput Uptime
ByteDance Seed ~$0.05 ~$0.10 — ~180ms ~40 tps ~99.9%
OpenAI ~$0.10 ~$0.20 — ~220ms ~35 tps 99.06%
Anthropic ~$0.09 ~$0.18 — ~210ms ~30 tps 99.28%
Google Cloud AI ~$0.08 ~$0.16 — ~250ms ~25 tps 99.9%

Try this model

Test Seed-2.0-Mini right here — free to start.

Seed-2.0-Mini
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call the model through the OpenAI-compatible API.

python 
                                        from openai import OpenAI
                                            
                                            client = OpenAI(
                                                api_key="YOUR_API_KEY",
                                                base_url="https://inference.example.com/v1"
                                            )
                                            
                                            response = client.chat.completions.create(
                                                model="bytedance-seed/seed-2-0-mini",
                                                messages=[
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ],
                                            )
                                            
                                            print(response.to_json())
                                        
                                    
                                        {
                                                "model": "bytedance-seed/seed-2-0-mini",
                                                "messages": [
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ]
                                            }

5 Core Capabilities

  • Conversational Chat

    Supports multi-turn dialogue, following instructions and maintaining basic context for everyday assistance and information-seeking conversations.

  • Multilingual Translation

    Translates text between major languages, enabling cross-lingual understanding for short messages, simple documents, and online content.

  • Document OCR

    Extracts machine-readable text from images or scanned documents, enabling search, editing, and downstream text processing of visual materials.

  • Image Captioning

    Generates concise descriptions of images, identifying key objects and scenes to support accessibility and content understanding.

  • Content Moderation

    Analyzes text or media for policy-violating, harmful, or unsafe content to support automated screening and compliance workflows.

6 Most Valuable Use Cases

  • High-volume Chatbots
  • Customer Support Triage
  • Knowledge Base Search
  • Alert & Log Monitoring
  • Cost-efficient Workflows
  • Lightweight Code Assistance

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the optimal model across providers based on latency, cost, and capability—without changing your integration or redeploying.

    One endpoint, best model.

  • Cost-Aware Orchestration

    Dynamically pick cheaper models for non-critical calls and reserve premium models for high-value tasks, cutting spend without sacrificing quality or reliability.

    Optimize every token.

  • Resilient Fallback Flows

    Define provider-agnostic fallback chains so requests transparently retry on alternate models when failures, rate limits, or timeouts occur—no custom glue code required.

    Stay up, even when they don’t.

  • Full-Stack Observability

    Get unified logs, traces, metrics, and cost breakdowns across all LLM providers in one place to debug issues faster and tune your workloads with confidence.

    See every token hop.

  • Task-Level Abstractions

    Describe tasks like chat, tools, RAG, or scoring once and let LLM.API translate them into provider-specific calls, simplifying logic and reducing integration drift.

    Code to tasks, not APIs.

  • High-Throughput Batch Jobs

    Run massive batches of prompts or evaluations through multiple models with automatic chunking, retries, and aggregation so you can ship experiments and pipelines faster.

    Scale experiments effortlessly.

When to Use — When NOT to Use

Use it if...

  • You need a lightweight general-purpose model for everyday chat and simple Q&A.
  • You need fast, low-cost inference for high-volume, low-complexity API requests.
  • Your use case involves simple classification, tagging, or short-text extraction tasks.
  • Your use case involves basic code help, such as small edits or snippets.
  • You need a small model to embed inside latency-sensitive consumer or mobile apps.
  • Your use case involves drafting short marketing copy, titles, or social media blurbs.

Avoid if...

  • You need top-tier reasoning quality for complex, multi-step analytical or scientific tasks.
  • You need reliable handling of very long documents, conversations, or context windows.
  • Your workload requires strong coding assistance across large codebases or complex refactors.
  • You need state-of-the-art performance on math, logic puzzles, or formal proofs.
  • Your workload requires highly nuanced instruction following with strict business or safety constraints.
  • You need specialized domain expertise, such as legal, medical, or financial advisory tasks.

Frequently Asked Questions

  • What is Seed-2.0-Mini?

    Seed-2.0-Mini is a compact text generation model from ByteDance Seed designed for fast, low-cost inference via the LLM.API platform.

  • What is Seed-2.0-Mini best suited for?

    Seed-2.0-Mini is best for lightweight chatbots, short-form content generation, and utility functions where low latency and cost matter more than maximal reasoning depth.

  • How is Seed-2.0-Mini priced on LLM.API?

    Seed-2.0-Mini uses LLM.API’s unified per-token or per-request pricing; check your LLM.API dashboard for the latest specific rates.

  • What is the context window of Seed-2.0-Mini?

    Seed-2.0-Mini supports a mid-sized context window suitable for short to medium conversations and prompts; consult LLM.API docs for the exact token limit.

  • How fast is Seed-2.0-Mini in terms of latency?

    Seed-2.0-Mini is optimized for low latency and high throughput, making it appropriate for real-time or interactive applications.

  • What modalities does Seed-2.0-Mini support?

    Seed-2.0-Mini is a text-only model, accepting text prompts and returning text completions through LLM.API.

  • How do I access Seed-2.0-Mini through LLM.API?

    Call the LLM.API completion or chat endpoint and specify the model name "Seed-2.0-Mini" in your request payload.

  • How does Seed-2.0-Mini compare to larger Seed models?

    Seed-2.0-Mini is cheaper and faster but generally less capable at complex reasoning and long-context tasks than larger Seed series models.

  • Does Seed-2.0-Mini support function calling or tool integration via LLM.API?

    If LLM.API exposes function-calling metadata, Seed-2.0-Mini can be used with it; check the LLM.API capabilities matrix for this model.

  • What are the main limitations of Seed-2.0-Mini?

    Seed-2.0-Mini may struggle with very long documents, nuanced multi-step reasoning, or highly specialized domain knowledge compared to larger frontier models.

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