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doubao · Balanced

Doubao Seed 2.1 Turbo

Added Jun 23, 2026

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Use in the app

Fast, lower-cost model in the Doubao Seed 2.1 family for everyday chat, coding assistance, document work, and high-throughput productivity tasks. Supports a 256k context window and up to 128k output tokens. Note: privacy and logging guarantees may be limited.

Input
Text
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.50
Output
$2.50

Reference prices as published by the model provider. API example

Specifications

Context window
256K
Max output
128K

Side by side

Doubao Seed 2.1 Turbo compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Doubao Seed 2.1 TurbodoubaoThis modelMiniMax M1 80KMiniMaxRemove
ProviderdoubaoMiniMax
Discovery tierBalancedBalanced
AddedJun 23, 2026Jan 8, 2025
Limits
Context window256K1MBest
Max output128K131.07KBest
Pricing, USD per 1M tokens
Input$0.50Best$0.61
Output$2.50$2.42Best
Benchmark indexes
Intelligence Index—11.7
Math Index—61.0
Capabilities
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Doubao Seed 2.1 Turbo
  • MiniMax M1 80K

Intelligence Index

  • Doubao Seed 2.1 Turbo—
  • MiniMax M1 80K11.7
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 61.0

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 57.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 8.9%
  • GPQA Diamond

    Graduate-level science questions

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 69.7%
  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 81.6%
  • IFBench

    Following precise output instructions

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 41.8%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 71.1%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 61.0%
  • AIME

    Competition mathematics

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 84.7%
  • MATH-500

    Competition math problems

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 98.0%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 3.0%
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 34.2%
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Doubao Seed 2.1 Turbo: —
    • MiniMax M1 80K: 57.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
0.0%

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "bytedance/doubao-seed-2.1-turbo",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="bytedance/doubao-seed-2.1-turbo",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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