qwen/qwen3.5-397b-a17b
262,144 context · $0.60/M input tokens · $3.60/M output tokens
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
従量課金
初期費用なし、使った分だけお支払い
以下のコード例を使用して API と連携してください:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3.5-397b-a17b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
| Specification | Value |
|---|---|
| Provider | Qwen |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 262144 tokens |
| Max Output | 65536 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.4 |
| Output | $2.3 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3.5-397b-a17b
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3.5-397b-a17b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "qwen/qwen3.5-397b-a17b",
"messages": [{"role": "user", "content": "Hello!"}]
}'
qwen/qwen3.5-397b-a17b
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
入力
$0.6 /M
出力
$3.6 /M
コンテキスト
262K
最大出力
66K
Vision
対応
ツール利用
対応
統合APIを通じてQwen3.5 397b A17bにアクセス — OpenAI互換、コールドスタートなし、透明な料金。
Playgroundを開くWaveSpeedAI の料金: 入力 100 万トークンあたり $0.60、出力 100 万トークンあたり $3.60。プロンプトキャッシュとバッチ処理は別途料金で、長く反復的なワークロードでは実効コストを下げられます。
Qwen3.5 397b A17b はリクエストあたり最大 262K のコンテキストトークンと最大 66K の出力トークンをサポートします。
はい。WaveSpeedAI は OpenAI 互換エンドポイント https://llm.wavespeed.ai/v1 で Qwen3.5 397b A17b を提供します。公式 OpenAI SDK のベース URL をこちらに変更し WaveSpeedAI の API キーを設定するだけで利用可能です。
WaveSpeedAI にサインインし、Access Keys で API キーを作成して、上に表示されているモデル ID を指定して https://llm.wavespeed.ai/v1/chat/completions にリクエストを送信してください。新規アカウントには Qwen3.5 397b A17b を試用できる無料クレジットが付与されます。