Doubao Seed 2.0 Pro 260215
doubao-seed-2-0-pro-260215Compare doubao-seed-2-0-pro-260215 API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 262.1K
- Maximum input window
- Max output
- 131.1K
- 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 2.0 Pro 260215
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 2.0 Pro 260215
把复杂任务拆成可检查的步骤
豆包 Seed 2.0 Pro 是 Seed 2.0 系列面向复杂推理和长链路任务的通用模型。它适合把多份资料放在一起比较、梳理方案中的依赖与矛盾，或在开发和业务流程中规划下一步。文字、截图和视频可以共同提供背景，让分析不局限于一段对话。
例如筹备一次产品发布，可以提交需求文档、演示材料和界面截图，让模型检查功能描述是否一致、哪些环节缺少证据、上线前还需要验证什么。复杂任务中，清楚的目标、约束和完成标准，比一句“帮我全面分析”更有助于形成可执行结果。
长链路任务怎样避免失去方向？
先定义阶段成果，再逐步推进。资料整理阶段标记事实与缺失信息，方案阶段说明取舍，执行阶段记录工具结果，最后按验收条件核对。长上下文有助于容纳更多材料，但仍应突出关键文件、版本和决策，避免把大量无关内容都塞进请求。
工具调用能替我完成哪些事？
取决于应用实际提供的工具。模型可以请求查询、运行检查或执行操作，但工具必须由程序执行，并把结果回传。没有实时数据或成功的执行结果时，答案只能作为分析或计划；把实际结果作为后续判断依据，才能持续推进任务。
怎样得到便于后续处理的结论？
使用清楚的字段和判定标准，可以通过结构化输出整理问题、证据、影响及下一步行动。对于重要结论，要求附上输入材料中的依据，并保留不确定项。
该版本已被上游列入下线计划，长期集成应提前对可用后续模型进行行为测试，特别检查工具协作和结果格式。
Use cases and prompting
给出完整目标与相关材料，例如：“比较这份需求文档、测试记录和演示截图，找出已经验证、只实现未验证、尚缺失的功能。逐项列出依据，不把计划当作完成；最后按依赖关系安排最短验证路径。”
任务较复杂时使用接口支持的思考模式，并预留回答预算。接入工具时明确可执行动作与验收标准，每一步都将真实结果回传，再由模型调整计划。需要长报告时先确定提纲，按章节展开，最后核对结论与输入证据是否一致。
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-2-0-pro-260215
What is doubao-seed-2-0-pro-260215?
Compare doubao-seed-2-0-pro-260215 API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call doubao-seed-2-0-pro-260215?
Create an API key with access to doubao-seed-2-0-pro-260215, 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-2-0-pro-260215 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-2-0-pro-260215?
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-2-0-pro-260215?
The model catalog lists a maximum output of 131072 tokens. Your request settings may set a lower limit.
How should I evaluate doubao-seed-2-0-pro-260215 for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.