qwen/qwen3.6-35b-a3b
262,144 context · $0.25/M input tokens · $2.00/M output tokens
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35B total parameters and 3B active parameters per token. It uses a hybrid sparse Mixture-of-Experts architecture that combines Gated DeltaNet linear attention with standard attention layers, giving it strong efficiency for coding, agentic workflows, long-context reasoning, and multimodal understanding. The model supports text, image, and video inputs, a 262K-token context window, thinking and non-thinking modes, function calling, and structured outputs.
Pay-per-use
No upfront costs, pay only for what you use
Use the following code examples to integrate with our API:
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/qwen3.6-35b-a3b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35B total parameters and 3B active parameters per token. It uses a hybrid sparse Mixture-of-Experts architecture combining Gated DeltaNet linear attention with standard attention layers, giving it strong efficiency for coding, agentic workflows, long-context reasoning, and multimodal understanding.
| Specification | Value |
|---|---|
| Provider | alibaba |
| Model Type | Chat Completions model |
| Architecture | Sparse MoE, 35B total / 3B active |
| Attention | Gated DeltaNet + standard attention |
| Modalities | text+image+video->text |
| Context Window | 262,144 tokens |
| Max Input | Not listed |
| Max Output | Not listed |
| Input | Text, Image, Video |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Structured Outputs | Supported |
| Thinking Mode | Supported |
| Release | April 2026 |
| Token Type | Cost |
|---|---|
| Input | $0.149 per million tokens |
| Output | $1.00 per million tokens |
Base URL: https://llm.wavespeed.ai/v1
API Endpoint: chat/completions
Model ID: qwen/qwen3.6-35b-a3b
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/qwen3.6-35b-a3b",
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/qwen3.6-35b-a3b",
"messages": [{"role": "user", "content": "Hello!"}]
}'
qwen/qwen3.6-35b-a3b
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35B total parameters and 3B active parameters per token. It uses a hybrid sparse Mixture-of-Experts architecture that combines Gated DeltaNet linear attention with standard attention layers, giving it strong efficiency for coding, agentic workflows, long-context reasoning, and multimodal understanding. The model supports text, image, and video inputs, a 262K-token context window, thinking and non-thinking modes, function calling, and structured outputs.
Input
$0.25 /M
Output
$2 /M
Context
262K
Vision
Supported
Tool Use
Supported
Access Qwen3.6 35b A3b through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Pricing on WaveSpeedAI: $0.25 per million input tokens and $2.00 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
Qwen3.6 35b A3b supports up to 262K tokens of context with up to — tokens of output per request.
Yes. WaveSpeedAI exposes Qwen3.6 35b A3b through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Qwen3.6 35b A3b before paying per token.