Doubao Seed 2.1 Turbo: context, capabilities and where to run it

Prices from official vendor price lists · October 2026

ByteDance does not publish a token price for Doubao Seed 2.1 Turbo, so cost depends on where it is hosted. Recorded here for reasoning.

Capabilities
Text & chatReasoningTool calling
Price / mo
API only

Doubao Seed 2.1 Turbo is an AI model from ByteDance. The vendor does not publish a public per-token price, so the cost cells are left empty rather than guessed.

Capabilities recorded in this rating: text & chat, reasoning, tool calling, low latency, multilingual. Access is through the API rather than a consumer subscription.

API priceNot publishedper 1M tokens, in / out
ContextNot publishedtokens per conversation
VendorByteDanceall models from this vendor
TierUnpricedno public rate card

Compared with alternatives

Good and poor fit

Good fit
  • Multi-step analysis, planning and code review, where the first plausible answer is often wrong.
  • High-volume routing, classification and autocomplete.
Poor fit
  • Long multi-step reasoning, where a larger model finishes in fewer attempts.
  • Anything requiring image input — this model does not accept it.

Related filters

Text & chat234 models for text generation and chat
Reasoning175 models that think before answering
Tool calling172 models that call your functions
Low latency76 small, fast models for volume
MultilingualAll 245 models work beyond English
ByteDance6 models from this vendor
All 245 modelsThe full rating with filters and prices

Frequently asked questions

How much does Doubao Seed 2.1 Turbo cost?

ByteDance does not publish a public per-token rate for this model, so the price cells here are empty rather than estimated.

What is the context window of Doubao Seed 2.1 Turbo?

Not published by the vendor.

What can Doubao Seed 2.1 Turbo do?

In this rating it is recorded with: text & chat, reasoning, tool calling, low latency, multilingual, proprietary API.

Is Doubao Seed 2.1 Turbo a good choice?

It depends on the job. See the good-fit and poor-fit lists above, and compare against the neighbouring models before committing.

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