

Qwen3.5 4B and Qwen3.5 27B side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Qwen3.5 4B and Qwen3.5 27B are both Alibaba Cloud models in the Text Generation category, available through the EmpirioLabs API.
| Spec | Qwen3.5 4B | Qwen3.5 27B |
|---|---|---|
| Model ID | qwen3-5-4b | qwen3-5-27b |
| Author | Alibaba Cloud | Alibaba Cloud |
| Released | Mar 2, 2026 | Feb 24, 2026 |
| Context window | 256K tokens | 258K tokens |
| Max output | 32,768 tokens | 64,000 tokens |
| Input | Text Image Video | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Schema | JSON Mode |
| Region | - | China |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1/completions POST /v1beta/models/qwen3-5-4b:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/qwen3-5-27b: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 4B | Qwen3.5 27B |
|---|---|---|
| temperature | 0 to 2 Default: 0.7 | 0 to 1.99 Default: 0.7 |
| top_p | 0.01 to 1 Default: 0.95 | 0 to 1 Default: 0.9 |
| max_tokens | 1 to 32768 Default: 8192 | 1 to 64000 |
| stop | string | string |
| enable_thinking | boolean Default: true | boolean Default: true |
| reasoning_effort | none, low, medium, high, max Default: medium | none, low, medium, high, max |
| thinking_budget | 1024 to 32768 Default: 4096 | 1 to 81920 |
| top_k | min 1 Default: 20 | 1 to 100 |
| min_p | 0 to 1 Default: 0 | - |
| frequency_penalty | -2 to 2 Default: 0 | - |
| presence_penalty | -2 to 2 Default: 0 | -2 to 2 |
| repetition_penalty | min 0.1 Default: 1 | 0.1 to 2 |
| seed | 0 to 2147483647 | 0 to 2147483647 |
| logprobs | boolean Default: false | boolean Default: false |
| top_logprobs | 0 to 20 | 0 to 5 Default: 0 |
| logit_bias | object | - |
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.
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 4B 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 qwen3-5-4b. Both models are called through the same endpoint. Set model to qwen3-5-4b or qwen3-5-27b. 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": "qwen3-5-4b",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Qwen3.5 4B is the newer release (Mar 2, 2026); Qwen3.5 27B was released on Feb 24, 2026. Qwen3.5 4B has the larger context window: 256K tokens, against 258K for Qwen3.5 27B. Qwen3.5 27B returns up to 64,000 output tokens per response, Qwen3.5 4B up to 32,768. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
Qwen3.5 4B is the newer release (Mar 2, 2026); Qwen3.5 27B was released on Feb 24, 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.