Endpoint coverage
Exposes 1 public endpoint(s): chat_completion.
Open-weight Qwen3.5 vision MoE (10B active); 256K context; OpenAI-compatible API
# Base URL
https://runapi.ai
# Endpoints
POST /v1/chat/completions
POST /v1/responses
POST /v1/messages
POST /v1beta/models/qwen3.5-122b-a10b:generateContent
POST /v1beta/models/qwen3.5-122b-a10b:streamGenerateContent
curl https://runapi.ai/v1/chat/completions \
-H "Authorization: Bearer $RUNAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3.5-122b-a10b",
"messages": [
{
"role": "user",
"content": "Read this screenshot of a failing dashboard, explain what the error message means, and suggest the code change that would fix it."
}
]
}'
from openai import OpenAI
client = OpenAI(
base_url="https://runapi.ai/v1",
api_key="your-runapi-key"
)
response = client.chat.completions.create(
model="qwen3.5-122b-a10b",
messages=[{"role": "user", "content": "Read this screenshot of a failing dashboard, explain what the error message means, and suggest the code change that would fix it."}]
)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://runapi.ai/v1",
apiKey: "your-runapi-key"
});
const response = await client.chat.completions.create({
model: "qwen3.5-122b-a10b",
messages: [{ role: "user", content: "Read this screenshot of a failing dashboard, explain what the error message means, and suggest the code change that would fix it." }]
});
9 versions available
Qwen3.5-122B-A10B is a native vision-language model from Alibaba's Qwen3.5 Medium series, released with open weights under Apache 2.0 on February 24, 2026. It is a Mixture-of-Experts model with hybrid linear attention, 122B total parameters, and 10B active per token. Alibaba ranks it second in the Qwen3.5 generation, behind Qwen3.5-397B-A17B.
Alibaba says its text capability exceeds Qwen3-235B-2507 and its vision capability exceeds Qwen3-VL-235B. It is a hybrid model with thinking on by default, a 262,144-token context window, and up to 65,536 output tokens. Function calling and structured outputs are supported.
On RunAPI, call qwen3.5-122b-a10b through the OpenAI-compatible Chat Completions endpoint (/v1/chat/completions) with an OpenAI SDK pointed at https://runapi.ai/v1. Images go in image_url parts inside messages[].content[].
Pick any model and generate in seconds.
| Provider | Alibaba |
| Model ID | qwen3.5-122b-a10b |
| Modality | Text |
| Task types | Synchronous |
| API endpoint | /v1/chat/completions |
| /v1/responses |
| /v1/messages | |
| /v1beta/models/qwen3.5-122b-a10b:generateContent | |
| /v1beta/models/qwen3.5-122b-a10b:streamGenerateContent | |
| Billing unit | 1K tokens |
| Catalog status | Operational |
Sign up for free and create an API key for qwen3.5-122b-a10b from the dashboard.
POST to /v1/chat/completions with the qwen3.5-122b-a10b model slug and your parameters.
Read the completed qwen3.5-122b-a10b response directly from the endpoint.
Exposes 1 public endpoint(s): chat_completion.
Metered by 1K tokens with no subscription requirement.
No request parameters are published for this endpoint.
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Alibaba ranks the 122B model second only to the 397B flagship. It activates 10B parameters per token against 17B for the flagship. Both have a 262,144-token context window, image input, and hybrid thinking.
Alibaba says the vision capability of Qwen3.5-122B-A10B exceeds Qwen3-VL-235B, and it also has twice the context window. Test it on your own images before you move a production workload.
By default, yes. It has thinking and non-thinking modes, and Alibaba's API turns thinking on unless the request switches it off. Thinking makes responses longer, so allow more time on sync requests.
Use RunAPI's OpenAI-compatible Chat Completions endpoint at https://runapi.ai/v1/chat/completions with your RunAPI API key and model set to qwen3.5-122b-a10b. Tools use the standard OpenAI tools format.
Pass the model ID shown in the quickstart.
Per-key rate limits scale with your usage tier. The pricing page shows current limits. If you need higher throughput, contact support to discuss tier upgrades.
Yes. Variant is a parameter in the request. Switch by changing the model ID — no code changes, no re-authentication, no separate billing setup. All variants share the same API key and request shape.
Where streaming is available, RunAPI streams end-to-end. LLM models support token-level streaming. Media models use async task polling or webhook callbacks for result delivery.
Open an issue on the public GitHub repo or email support at [email protected]. Include the task ID and model ID so the team can investigate the specific generation.
No. Your RunAPI API key is enough to access this variant and every other model in the catalog. You do not need accounts with the underlying provider.
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