

Qwen3.5 122B-A10B and Qwen3.5 9B side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Qwen3.5 122B-A10B and Qwen3.5 9B are both Alibaba Cloud models in the Text Generation category, available through the EmpirioLabs API.
| Spec | Qwen3.5 122B-A10B | Qwen3.5 9B |
|---|---|---|
| Model ID | qwen3-5-122b-a10b | qwen3-5-9b |
| Author | Alibaba Cloud | Alibaba Cloud |
| Released | Feb 24, 2026 | Feb 23, 2026 |
| Context window | 258K tokens | 256K tokens |
| Max output | 64,000 tokens | 32,768 tokens |
| Input | Text Image Video | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Mode | JSON Schema |
| Region | 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 /v1/completions POST /v1beta/models/qwen3-5-9b: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 9B |
|---|---|---|
| temperature | 0 to 1.99 Default: 0.7 | 0 to 2 Default: 0.7 |
| top_p | 0 to 1 Default: 0.9 | 0.01 to 1 Default: 0.95 |
| max_tokens | 1 to 64000 | 1 to 32768 Default: 8192 |
| stop | string | string |
| enable_thinking | boolean Default: true | boolean Default: true |
| reasoning_effort | none, low, medium, high, max | none, low, medium, high, max Default: medium |
| thinking_budget | 1 to 81920 | 1024 to 32768 Default: 4096 |
| seed | 0 to 2147483647 | 0 to 2147483647 |
| top_k | 1 to 100 | min 1 Default: 20 |
| presence_penalty | -2 to 2 | -2 to 2 Default: 0 |
| repetition_penalty | 0.1 to 2 | min 0.1 Default: 1 |
| n | 1 to 4 Default: 1 | - |
| logprobs | boolean Default: false | boolean Default: false |
| top_logprobs | 0 to 5 Default: 0 | 0 to 20 |
| vl_high_resolution_images | boolean Default: true | - |
| max_pixels | 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, streaming, function tools, structured JSON output, seed control, and thinking mode on by default. Use reasoning_effort or thinking_budget for bounded thinking, or enable_thinking=false for direct answers. Automatic cache reads are billed at the cached-input rate when reported by the model service. Explicit cache controls are not supported.
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 qwen3-5-9b. 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 9B was released on Feb 23, 2026. Qwen3.5 9B has the larger context window: 256K tokens, against 258K for Qwen3.5 122B-A10B. Qwen3.5 122B-A10B returns up to 64,000 output tokens per response, Qwen3.5 9B up to 32,768. 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 9B was released on Feb 23, 2026.
The two models are priced on different units or tiers, so compare the live rate cards on this page. They 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.