Direct
Direct upstream connection — best when you need native behavior and the full context window.
| Input context | Input | Output | Cache read |
|---|---|---|---|
| ≤ 32K | 0.09/M | 0.53/M | 0.02/M |
| 32K – 128K | 0.13/M | 0.79/M | 0.03/M |
| > 128K | 0.26/M | 1.59/M | 0.05/M |

doubao-seed-2-0-lite-260215A balanced model for high-frequency enterprise scenarios that balances performance and cost, with overall capabilities surpassing the previous generation Doubao-Seed-1.8. It is well-suited for production tasks such as unstructured information processing, content creation, search recommendation, and data analysis, supporting long context, multi-source information fusion, multi-step instruction execution, and high-fidelity structured output. It significantly optimizes costs while ensuring stable performance.
The same model is available through multiple service channels — choose based on latency, reliability and cost.
Prices in $ / 1M tokensprovider field to the request body, for example "provider": { "channel": "direct" }. Valid values are direct / stable / economical; omit it to use the default channel.Direct upstream connection — best when you need native behavior and the full context window.
| Input context | Input | Output | Cache read |
|---|---|---|---|
| ≤ 32K | 0.09/M | 0.53/M | 0.02/M |
| 32K – 128K | 0.13/M | 0.79/M | 0.03/M |
| > 128K | 0.26/M | 1.59/M | 0.05/M |
Doubao-Seed-2.0-lite is a balanced model launched by ByteDance for high-frequency enterprise scenarios, balancing performance and cost, with overall capabilities surpassing the previous generation Doubao-Seed-1.8. It is well-suited for production workloads such as unstructured information processing, content creation, search and recommendation, and data analysis, supporting long context, multi-source information fusion, multi-step instruction execution, and high-fidelity structured output.
The new version from May 2026 makes it the first omni-modal understanding model in the Doubao large model family—supporting native unified understanding of video, image, audio, and text. It significantly surpasses the Pro version released in February on advanced subject reasoning benchmarks such as physics (HiPhO) and medicine (MedXpertQA), and reaches SOTA levels in fine-grained perception (BabyVision, WorldVQA) and embodied understanding (ERQA).
SeaWhale AI provides Doubao-Seed-2.0-lite through an OpenAI-compatible interface, supporting multimodal input, tool calling, and streaming output.
Get the API key · Model ID:
doubao-seed-2-0-lite-260215
This is the biggest upgrade in the May version: video, image, audio, and text are natively and uniformly understood within the same model, rather than stitching together multiple models. This makes cross-modal associative reasoning possible.
On advanced subject reasoning benchmarks such as physics (HiPhO) and medicine (MedXpertQA), the new lite version significantly surpasses the Pro version released in February, demonstrating that the capability improvements in this version are substantial.
Reaches SOTA levels on fine-grained perception benchmarks such as BabyVision and WorldVQA and the ERQA embodied understanding benchmark, making it suitable for scenarios requiring precise visual judgment.
lite's core focus remains high-frequency production work: unstructured information processing, content creation, search and recommendation, and data analysis—these scenarios require stability, speed, and low cost.
| Use Case | Description |
|---|---|
| Omni-modal content understanding | Unified processing of video, audio, image, and text |
| High-frequency information processing | Extraction and organization of large-scale unstructured data |
| Content creation | Batch generation of copy, creative assets, and marketing content |
| Search and recommendation | Relevance judgment and content understanding |
| Subject reasoning | Professional domain problems such as physics and medicine |
| Fine-grained visual judgment | Scenarios requiring precise visual difference recognition |
| Capability | Doubao-Seed-2.0-lite | Doubao-Seed-2.0-pro |
|---|---|---|
| Model ID | doubao-seed-2-0-lite-260215 |
doubao-seed-2-0-pro-260215 |
| Positioning | Balanced for high-frequency enterprise scenarios | Flagship all-purpose general model |
| Context window | 1 million tokens | 1 million tokens |
| Max output | 65.5K tokens | 65.5K tokens |
| Modalities | Omni-modal (video/image/audio/text) | Text, image |
| Advanced subject reasoning | Significantly surpasses the February Pro version | Strong |
| Focus | Balance of performance and cost | Complex reasoning and long-chain execution |
The Doubao series is priced in tiers by input length (32K / 128K / longer); please refer to the real-time price card at the top of the page for exact pricing.
1. Create a SeaWhale AI API key Generate a key in the console and top up your balance.
2. Try it first on multimodal tasks The lite version's omni-modal understanding capability is the biggest differentiator of this generation. For video and audio related scenarios, you can use it directly without stitching together multiple specialized models.
3. Call the API
curl -X POST https://api.seawhaleai.com/v1/chat/completions \
-H 'Authorization: Bearer YOUR_API_KEY' \
-H 'Content-Type: application/json' \
-d '{
"model": "doubao-seed-2-0-lite-260215",
"messages": [{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://example.com/chart.png"}},
{"type": "text", "text": "Read the values for each quarter in this chart and describe the trend."}
]
}],
"stream": true
}'
Why does the lite version outperform the Pro version on some benchmarks? lite received a new version upgrade in May 2026, becoming the first omni-modal understanding model in the Doubao family. On advanced subject reasoning such as physics and medicine, the new lite version significantly surpasses the Pro version released in February.
What exactly does "omni-modal" include? Native unified understanding of video, image, audio, and text—four modalities processed within the same model, rather than stitching together multiple specialized models.
When should you still use Pro? When you need the most complex multi-step planning, long-chain execution, and simultaneous satisfaction of multiple constraints, the Pro version is still more suitable.
What are the context and output limits? 1 million token context, maximum output of 65,500 tokens.
Why are prices divided into three tiers? The Doubao series is priced in tiers by input token length (32K / 128K / longer). The unit price for short inputs is significantly lower, making context length control an effective way to reduce costs.
Is it suitable for large-scale deployment? Yes. lite is precisely the tier designed for high-frequency enterprise scenarios, significantly optimizing costs while ensuring stable performance.
doubao-seed-2-0-lite-260215https://api.seawhaleai.com/v2/"provider": { "channel": "direct" }SeaWhale AI is compatible with the OpenAI API protocol, so you can call it with the OpenAI SDK or plain HTTP requests. Streaming is enabled by default.
About the provider parameter (optional, a SeaWhale AI extension): most models are served over several channels that differ slightly in price and reliability. Add a provider field to the request body to pick one; omit it and the system selects the default channel — normal calls are unaffected.
provideris not part of the official OpenAI protocol — it is a SeaWhale AI extension that only takes effect on this platform. The OpenAI SDK allows custom fields like this to pass through; see the examples below.
| Value | Channel | Best for |
|---|---|---|
direct | Direct | The official upstream link, for native behavior and the full context window |
stable | Preferred | Balanced availability and speed — a good default for production traffic |
economical | Economy | Cost first, well suited to batch processing and price-sensitive workloads |
Available channels and their prices are listed under "Pricing" above (channels vary by model). Additional notes:
"provider": { "channel": "direct" }.extra_body; in Node.js put it directly on the request object and it passes through. In TypeScript projects, add a // @ts-expect-error line to skip the type check.curl https://api.seawhaleai.com/v2/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <API_KEY>" \
-d '{
"model": "doubao-seed-2-0-lite-260215",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
],
"provider": { "channel": "direct" },
"stream": true
}'
# provider is optional — remove this line to use the default channelfrom openai import OpenAI
client = OpenAI(
base_url="https://api.seawhaleai.com/v2",
api_key="<API_KEY>",
)
stream = client.chat.completions.create(
model="doubao-seed-2-0-lite-260215",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"},
],
stream=True,
# Optional: pick a service channel; omit to use the default
extra_body={"provider": {"channel": "direct"}},
)
for chunk in stream:
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end="", flush=True)import OpenAI from 'openai'
const client = new OpenAI({
baseURL: 'https://api.seawhaleai.com/v2',
apiKey: '<API_KEY>',
})
const stream = await client.chat.completions.create({
model: 'doubao-seed-2-0-lite-260215',
messages: [
{ role: 'system', content: 'You are a helpful assistant.' },
{ role: 'user', content: 'Hello!' },
],
stream: true,
// Optional: pick a service channel; omit to use the default
// @ts-expect-error provider is a SeaWhale AI extension, not in the OpenAI SDK types
provider: { channel: 'direct' },
})
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? '')
}