

Gemma 4 26B-A4B and Qwen3.5 4B side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Gemma 4 26B-A4B from Google and Qwen3.5 4B from Alibaba Cloud are both in the Text Generation category, available through the EmpirioLabs API.
| Spec | Gemma 4 26B-A4B | Qwen3.5 4B |
|---|---|---|
| Model ID | gemma-4-26b-a4b | qwen3-5-4b |
| Author | Alibaba Cloud | |
| Released | Mar 31, 2026 | Mar 2, 2026 |
| Context window | 256K tokens | 256K tokens |
| Max output | 32,768 tokens | 32,768 tokens |
| Input | Text Image Video | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Schema | JSON Schema |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1/completions POST /v1beta/models/gemma-4-26b-a4b:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1/completions POST /v1beta/models/qwen3-5-4b: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 | Gemma 4 26B-A4B | Qwen3.5 4B |
|---|---|---|
| temperature | 0 to 2 Default: 1 | 0 to 2 Default: 0.7 |
| top_p | 0.01 to 1 Default: 0.95 | 0.01 to 1 Default: 0.95 |
| max_tokens | 1 to 32768 Default: 8192 | 1 to 32768 Default: 8192 |
| stop | string | string |
| reasoning_effort | none, low, medium, high, max Default: medium | none, low, medium, high, max Default: medium |
| enable_thinking | boolean Default: true | boolean Default: true |
| thinking_budget | 128 to 32768 Default: 4096 | 1024 to 32768 Default: 4096 |
| top_k | min 1 Default: 20 | min 1 Default: 20 |
| presence_penalty | -2 to 2 Default: 0 | -2 to 2 Default: 0 |
| frequency_penalty | -2 to 2 Default: 0 | -2 to 2 Default: 0 |
| repetition_penalty | min 0.1 Default: 1 | min 0.1 Default: 1 |
| seed | 0 to 2147483647 | 0 to 2147483647 |
| logprobs | boolean Default: false | boolean Default: false |
| top_logprobs | 0 to 20 | 0 to 20 |
| logit_bias | object | object |
| tools | array | array |
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, 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.
Gemma 4 26B-A4B 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 gemma-4-26b-a4b. Both models are called through the same endpoint. Set model to gemma-4-26b-a4b or qwen3-5-4b. 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": "gemma-4-26b-a4b",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Prompt tests and comparison runs that cover both models.
Gemma 4 26B-A4B is the newer release (Mar 31, 2026); Qwen3.5 4B was released on Mar 2, 2026. Both models have a context window of 256K tokens. Qwen3.5 4B lists the lower rate for Input (per 1M prompt tokens) and Output (per 1M generated tokens). The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
Gemma 4 26B-A4B is the newer release (Mar 31, 2026); Qwen3.5 4B was released on Mar 2, 2026.
Qwen3.5 4B lists the lower rate for Input (per 1M prompt tokens) and Output (per 1M generated tokens). 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.