Doubao Seed 2.0 Lite
Doubao Seed 2.0 Lite في مصر. قارن أسعار API، والمزوّد، وطول context، والقدرات، وuse cases، وlatency، والبدائل. high-volume chat, classification, lightweight agent steps. ¥0.6 / 1M tokens / ¥3.60 / 1M tokens. 256k tokens.
| Input length | Input / 1M | Output / 1M | Cache hit / 1M |
|---|---|---|---|
| 0 - 32k | ¥0.6 | ¥3.60 | ¥0.12 |
| 32k - 128k | ¥0.9 | ¥5.40 | ¥0.18 |
| 128k - 256k | ¥1.80 | ¥10.80 | ¥0.36 |
ما هو Doubao Seed 2.0 Lite في NextModel؟
Doubao Seed 2.0 Lite في مصر. قارن أسعار API، والمزوّد، وطول context، والقدرات، وuse cases، وlatency، والبدائل. high-volume chat, classification, lightweight agent steps. ¥0.6 / 1M tokens / ¥3.60 / 1M tokens. 256k tokens.
أفضل الاستخدامات
- high-volume chat
- classification
- lightweight agent steps
مثال OpenAI-compatible
حافظ على أسلوب OpenAI SDK، ووجّه base_url إلى NextModel، واستخدم معرّف الكتالوج doubao-seed-2-0-lite.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.nextmodel.app/v1"
)
resp = client.chat.completions.create(
model="doubao-seed-2-0-lite",
messages=[{"role": "user", "content": "Hello from NextModel"}]
)
print(resp.choices[0].message.content)بدائل مشابهة
MiniMax M3 is available only through the Volcengine Agent Plan (no public ARK price list); its listed price tracks the OpenRouter reference rate for the same model.
Doubao Seed 2.0 Mini is the lowest-cost production model currently exposed through the NextModel public gateway. It is a practical default for Chinese Q&A, classification, summarization, and lightweight multimodal tasks.
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
FAQ
Doubao Seed 2.0 Lite FAQ
What is Doubao Seed 2.0 Lite best for?
High-volume Chinese chat, classification, and lightweight agent steps where cost matters more than peak reasoning quality.
How is Doubao Seed 2.0 Lite priced?
Tiered by input length: ¥0.6/¥3.6 per 1M input/output tokens up to 32K tokens, rising to ¥1.8/¥10.8 above 128K tokens.