

Qwen3.5 122B-A10B and Qwen3.5 397B-A17B side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Qwen3.5 122B-A10B and Qwen3.5 397B-A17B are both Alibaba Cloud models in the Text Generation category, available through the EmpirioLabs API.
| Spec | Qwen3.5 122B-A10B | Qwen3.5 397B-A17B |
|---|---|---|
| Model ID | qwen3-5-122b-a10b | qwen3-5-397b-a17b |
| Author | Alibaba Cloud | Alibaba Cloud |
| Released | Feb 24, 2026 | Feb 16, 2026 |
| Context window | 258K tokens | 258K tokens |
| Max output | 64,000 tokens | 64,000 tokens |
| Input | Text Image Video | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Mode | JSON Mode |
| Region | China | China |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/qwen3-5-122b-a10b:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/qwen3-5-397b-a17b:generateContent |
| Capabilities |
Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.
Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.
| Parameter | Qwen3.5 122B-A10B | Qwen3.5 397B-A17B |
|---|---|---|
| temperature | 0 to 1.99 Default: 0.7 | 0 to 1.99 Default: 0.7 |
| top_p | 0 to 1 Default: 0.9 | 0 to 1 Default: 0.9 |
| max_tokens | 1 to 64000 | 1 to 64000 |
| stop | string | string |
| enable_thinking | boolean Default: true | boolean Default: true |
| reasoning_effort | none, low, medium, high, max | none, low, medium, high, max |
| thinking_budget | 1 to 81920 | 1 to 81920 |
| seed | 0 to 2147483647 | 0 to 2147483647 |
| top_k | 1 to 100 | 1 to 100 |
| presence_penalty | -2 to 2 | -2 to 2 |
| repetition_penalty | 0.1 to 2 | 0.1 to 2 |
| n | 1 to 4 Default: 1 | 1 to 4 Default: 1 |
| logprobs | boolean Default: false | boolean Default: false |
| top_logprobs | 0 to 5 Default: 0 | 0 to 5 Default: 0 |
| vl_high_resolution_images | boolean Default: true | boolean Default: true |
| max_pixels | 4096 to 16777216 Default: 2621440 | 4096 to 16777216 Default: 2621440 |
Supports text, image, and video input. Web search is available through tool_web_search and adds $0.01 per request when enabled. Thinking tokens are billed as output tokens.
Supports text, image, and video input. Web search is available through tool_web_search and adds $0.01 per request when enabled. Thinking tokens are billed as output tokens.
Qwen3.5 122B-A10B serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id qwen3-5-122b-a10b. Both models are called through the same endpoint. Set model to qwen3-5-122b-a10b or qwen3-5-397b-a17b. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-5-122b-a10b",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Qwen3.5 122B-A10B is the newer release (Feb 24, 2026); Qwen3.5 397B-A17B was released on Feb 16, 2026. Both models have a context window of 258K tokens. Both models list the same rate for Web search (per request when enabled). The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
Qwen3.5 122B-A10B is the newer release (Feb 24, 2026); Qwen3.5 397B-A17B was released on Feb 16, 2026.
Both models list the same rate for Web search (per request when enabled). Both live rate cards are on this page and always match what the API charges.
Yes. Both models use POST /v1/chat/completions with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.
Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.
Check out our pricing or reach out if you want your own model deployed on our stack.