Is Seed Evolving a standalone AI model?

No. Seed Evolving is a development methodology and training framework rather than a separately deployed model like Seedance or Seedream.

How does Seed Evolving improve model performance?

It uses automated evaluation systems, synthetic data generation, reinforcement learning, and iterative training cycles to continuously refine future model generations.

Which models benefit from Seed Evolving?

The approach appears to support the broader Seed ecosystem, including Seed 2.0, Seed 2.1, Seed1.8, Seedance, and other multimodal models developed by ByteDance.

Does Seed Evolving support multimodal AI?

Yes. The Seed ecosystem is designed around multimodal understanding across text, image, audio, video, and agent-interaction environments.

How is Seed Evolving different from traditional AI training?

Traditional AI training often relies on static datasets and periodic releases, while Seed Evolving introduces continuous feedback loops that allow models to contribute to future model improvements.

Why is Seed Evolving important for AI agents?

The framework is designed to improve long-horizon planning, tool use, reasoning, coding, and real-world task execution, which are critical capabilities for advanced AI agents.

Uygun Fiyatlı Doubao-Seed-Evolving API | text-to-text

Q: What is Seed Evolving?

Seed Evolving is ByteDance's self-improving AI development framework that enables Seed models to help improve future generations through evaluation, data generation, training, and infrastructure feedback loops.

Doubao-Seed-Evolving için Playground

Doubao-Seed-Evolving'ın Playground'unu keşfedin — modelleri test etmek ve sorguları gerçek zamanlı olarak çalıştırmak için etkileşimli bir ortam. Prompt'ları deneyin, parametreleri ayarlayın ve geliştirmeyi hızlandırmak ve kullanım senaryolarını doğrulamak için anında yineleyin.

Technical Specifications of Seed Evolving

Item	Doubao Seed Evolving
Provider	ByteDance Seed Team
Model Type	Self-improving multimodal foundation model framework
Family	Seed / Doubao Ecosystem
Modalities	Text, Image, Video, Audio, Agent Tasks
Architecture Focus	Self-evolution through evaluation, data generation, training, and infrastructure feedback loops
Primary Goal	Continuous model improvement and autonomous capability expansion
Availability	Research framework integrated into Seed family development
Latest Related Generation	Seed 2.1
Deployment Focus	Agent systems, reasoning, multimodal understanding, real-world task execution

What is Seed Evolving?

"Seed Evolving" is not a standalone commercial model like Seedance or Seedream. Instead, it refers to ByteDance Seed's self-evolving AI development framework that continuously improves future generations of Seed models through automated evaluation, data generation, reinforcement learning, training optimization, and infrastructure feedback. ByteDance describes this internally as a "Seed-for-Seed" lifecycle where models help improve future models.

The concept became more visible with the release of Seed 2.1, where ByteDance discussed a self-evolving lifecycle composed of:

Evaluation Loop
Data Loop
Training Loop
Infrastructure Loop

These systems allow newer Seed models to participate in generating training signals and improving subsequent model generations.

Main Features of Seed Evolving

Self-improving training pipeline where models contribute to future model development.
Automated evaluation systems that identify weaknesses and generate improvement targets.
Agent-centric optimization designed for long-horizon task execution rather than simple chat interactions.
Multimodal learning across text, images, audio, video, and GUI environments.
Real-world task orientation focusing on tool use, coding, browsing, and multi-step workflows.
Scalable model evolution framework intended to improve performance without relying solely on manual dataset construction.

Benchmark Performance

ByteDance has not published benchmark numbers specifically for "Seed Evolving" because it is a methodology rather than a deployable model.

Performance is reflected through newer Seed-family models:

Benchmark	Seed Family Result
BrowseComp	77.3
τ²-Bench Retail	90.4
τ²-Bench Telecom	94.2
Terminal Bench 2.0	55.8

These benchmark improvements are cited as outcomes of the broader Seed 2.0 development process and evolving training ecosystem.

Seed Evolving vs Traditional Model Development

Feature	Seed Evolving	Traditional AI Training
Evaluation	Continuous automated feedback	Periodic human evaluation
Data Creation	Model-assisted generation	Mostly human-curated
Improvement Cycle	Continuous	Release-based
Agent Learning	Core focus	Often secondary
Multimodal Optimization	Native	Frequently separate systems
Scaling Strategy	Self-reinforcing loops	Larger datasets and comput

Doubao-Seed-Evolving için Fiyatlandırma

Doubao-Seed-Evolving için çeşitli bütçelere ve kullanım ihtiyaçlarına uygun rekabetçi fiyatlandırmayı keşfedin. Esnek planlarımız sadece kullandığınız kadar ödeme yapmanızı sağlar ve ihtiyaçlarınız büyüdükçe kolayca ölçeklendirme imkanı sunar. Doubao-Seed-Evolving'in maliyetleri yönetilebilir tutarken projelerinizi nasıl geliştirebileceğini keşfedin.

Model	Comet Price (USD / M Tokens)	Official Price (USD / M Tokens)	Discount
doubao-seed-evolving	Giriş:$0.66672/M Çıktı:$3.3336/M	Giriş:$0.8334/M Çıktı:$4.167/M	-20%

Doubao-Seed-Evolving için örnek kod ve API

Doubao-Seed-Evolving için kapsamlı örnek kodlara ve API kaynaklarına erişerek entegrasyon sürecinizi kolaylaştırın. Ayrıntılı dokümantasyonumuz adım adım rehberlik sağlayarak projelerinizde Doubao-Seed-Evolving'in tüm potansiyelinden yararlanmanıza yardımcı olur.

# Get your CometAPI key from https://www.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

set -eo pipefail

curl -sS --retry 3 --retry-delay 2 --retry-all-errors https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "doubao-seed-evolving",
    "max_completion_tokens": 2048,
    "reasoning_effort": "medium",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "image_url",
            "image_url": {
              "url": "https://ark-project.tos-cn-beijing.ivolces.com/images/view.jpeg"
            }
          },
          {
            "type": "text",
            "text": "Describe the scene in two concise bullet points and infer one likely use case."
          }
        ]
      }
    ]
  }' | jq '.choices[0].message.content // .error // .'

cURL Code Example

# Get your CometAPI key from https://www.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

set -eo pipefail

curl -sS --retry 3 --retry-delay 2 --retry-all-errors https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "doubao-seed-evolving",
    "max_completion_tokens": 2048,
    "reasoning_effort": "medium",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "image_url",
            "image_url": {
              "url": "https://ark-project.tos-cn-beijing.ivolces.com/images/view.jpeg"
            }
          },
          {
            "type": "text",
            "text": "Describe the scene in two concise bullet points and infer one likely use case."
          }
        ]
      }
    ]
  }' | jq '.choices[0].message.content // .error // .'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://www.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

completion = client.chat.completions.create(
    model="doubao-seed-evolving",
    max_completion_tokens=2048,
    extra_body={"reasoning_effort": "medium"},
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://ark-project.tos-cn-beijing.ivolces.com/images/view.jpeg"
                    },
                },
                {
                    "type": "text",
                    "text": "Describe the scene in two concise bullet points and infer one likely use case.",
                },
            ],
        }
    ],
)

print(completion.choices[0].message.content)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://www.cometapi.com/console/token, and paste it here
const api_key = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const base_url = "https://api.cometapi.com/v1";

const openai = new OpenAI({
  apiKey: api_key,
  baseURL: base_url,
});

async function main() {
  const completion = await openai.chat.completions.create({
    model: "doubao-seed-evolving",
    max_completion_tokens: 2048,
    reasoning_effort: "medium",
    messages: [
      {
        role: "user",
        content: [
          {
            type: "image_url",
            image_url: {
              url: "https://ark-project.tos-cn-beijing.ivolces.com/images/view.jpeg"
            }
          },
          {
            type: "text",
            text: "Describe the scene in two concise bullet points and infer one likely use case."
          }
        ]
      }
    ],
  });

  console.log(completion.choices[0].message.content);
}

main();

Doubao-Seed-Evolving Sürümleri

Doubao-Seed-Evolving'nın birden fazla anlık görüntüye sahip olmasının nedeni; güncellemeler sonrası çıktı varyasyonları nedeniyle tutarlılık için eski anlık görüntülere ihtiyaç duyulması, geliştiricilere uyum ve geçiş için bir geçiş dönemi sağlanması ve kullanıcı deneyimini optimize etmek için küresel veya bölgesel uç noktalara karşılık gelen farklı anlık görüntüler içerebilir. Sürümler arasındaki detaylı farklar için lütfen resmi belgelere başvurun.

Version
doubao-seed-evolving

Doubao-Seed-Evolving