Doubao Seed 2.1 Turbo 260628
doubao-seed-2-1-turbo-260628Compare doubao-seed-2-1-turbo-260628 API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 262.1K
- Maximum input window
- Max output
- 262.1K
- Maximum tokens per response
- Modalities
- →
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
Doubao tokenizerPerformance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Doubao Seed 2.1 Turbo 260628
This model is not included in the current benchmark snapshot.
Missing models or measurements are not zero scores.
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About Doubao Seed 2.1 Turbo 260628
把用户描述整理成明确的处理任务
豆包 Seed 2.1 Turbo 能阅读文字，也能理解图片和视频中的内容。用户发来一段操作描述、几张报错截图或一段录屏时，可以让它先整理问题经过，再提取关键信息、归类诉求并给出下一步建议，适合客服、运营和内部业务助手。
处理工单时，模型可以把不同表达的同类问题归并起来，按发生条件、影响范围和缺失信息输出摘要。面对截图或视频，应明确让它观察哪些内容，例如订单状态、错误提示、操作顺序，而不是要求它凭画面推断整个系统。回复用户时，也可以指定语言风格、信息边界和需要追问的问题，让答案更贴近实际服务流程。
它具备深度思考、GUI 任务处理、工具调用和结构化输出能力。应用可以为它提供订单查询、知识检索或界面操作工具，使它依据最新结果继续处理问题。把工单类型、摘要、待补充信息和建议动作定义为固定字段，方便后续分派与统计。具体动作完成后，应以工具返回的状态判断是否成功。
需要复杂判断时，可以启用深度思考，并给最终回答留下足够预算。日常分类和短回复则应保持输入与输出目标清楚。涉及多条工单时，保留各自编号，让模型逐条给出依据；这比把所有问题混在一段结论里更便于追踪和复核。
Use cases and prompting
工单整理示例
“请根据这份用户描述和截图生成工单摘要。输出问题类别、用户已做的操作、图中能确认的状态、还需补充的信息和建议下一步。不要把尚未查询的订单状态写成事实。对用户的追问控制在三条以内，语气简洁友好。”
常见问题
- 用户只有一张截图，信息不够怎么办？先说明截图里能看见的现象，再追问发生时间、操作步骤等必要条件。
- 如何接入自动分派？把类别和优先级设为枚举字段，通过结构化输出交给分派程序处理。
- 模型说已查到订单，能直接采信吗？检查是否实际调用查询工具，并以返回记录为依据；必要时将记录编号一并保留。
API access
API documentation
Code samples
/v1/chat/completions| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| Volcengine | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about doubao-seed-2-1-turbo-260628
What is doubao-seed-2-1-turbo-260628?
Compare doubao-seed-2-1-turbo-260628 API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call doubao-seed-2-1-turbo-260628?
Create an API key with access to doubao-seed-2-1-turbo-260628, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is doubao-seed-2-1-turbo-260628 priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
What is the context window of doubao-seed-2-1-turbo-260628?
The model catalog lists a context window of 262144 tokens. Check the selected endpoint for request limits.
What is the maximum output of doubao-seed-2-1-turbo-260628?
The model catalog lists a maximum output of 262144 tokens. Your request settings may set a lower limit.
How should I evaluate doubao-seed-2-1-turbo-260628 for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.