Qwen3.8 Max 0902 vs Qwen3.7 Max

Qwen3.8 Max 0902 vs Qwen3.7 Max at a glance

Qwen3.8 Max 0902 and Qwen3.7 Max are both Alibaba Cloud models in the Text Generation category, available through the EmpirioLabs API.

Key differences

• Qwen3.8 Max 0902 is the newer release (Sep 2, 2026); Qwen3.7 Max was released on May 21, 2026.
• Both models have a context window of 983.6K tokens.
• Qwen3.8 Max 0902 returns up to 131,072 output tokens per response, Qwen3.7 Max up to 65,536.
• Input types only Qwen3.8 Max 0902 accepts: Image, Video.
• Capabilities listed only for Qwen3.8 Max 0902: vision, multimodal, structured output.
• Qwen3.8 Max 0902 lists the lower rate for Input (per 1M prompt tokens) and Output (per 1M generated tokens).

Qwen3.8 Max 0902 vs Qwen3.7 Max: specs

Qwen3.8 Max 0902 vs Qwen3.7 Max: API pricing

Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.

Qwen3.8 Max 0902 vs Qwen3.7 Max: API parameters

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.

Qwen3.8 Max 0902 vs Qwen3.7 Max: limits and notes

Qwen3.8 Max 0902

Text, image, and video input are supported. Web search, web extractor, code interpreter, text-to-image search, and image-to-image search are optional built-in tools exposed through tool_* parameters. Web search, text-to-image search, and image-to-image search add $0.02 for each invoked call; web extractor and code interpreter run at no extra cost. Web extractor requires web search, and both web extractor and code interpreter require thinking. A single request can invoke a tool more than once, and each invoked call is billed. Thinking tokens are billed as output tokens. This id is pinned to the September 2, 2026 snapshot and will not change. The rolling qwen3-8-max id serves the same build since September 5, 2026 and will move to future snapshots.

Qwen3.7 Max

Text input only. Web search, web extractor, and code interpreter are optional built-in tools exposed through tool_* parameters. Each built-in tool call adds $0.02 when invoked. Thinking tokens are billed as output tokens.

How to call Qwen3.8 Max 0902 and Qwen3.7 Max

Qwen3.8 Max 0902 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 qwen3-8-max-0902. Both models are called through the same endpoint. Set model to qwen3-8-max-0902 or qwen3-7-max. 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": "qwen3-8-max-0902",
    "messages": [
      {"role": "user", "content": "Write a haiku about the ocean."}
    ]
  }'

Qwen3.8 Max 0902 vs Qwen3.7 Max: common questions

What is the difference between Qwen3.8 Max 0902 and Qwen3.7 Max?

Qwen3.8 Max 0902 is the newer release (Sep 2, 2026); Qwen3.7 Max was released on May 21, 2026. Both models have a context window of 983.6K tokens. Qwen3.8 Max 0902 returns up to 131,072 output tokens per response, Qwen3.7 Max up to 65,536. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.

Which is newer, Qwen3.8 Max 0902 or Qwen3.7 Max?

Qwen3.8 Max 0902 is the newer release (Sep 2, 2026); Qwen3.7 Max was released on May 21, 2026.

Which has the lower rate, Qwen3.8 Max 0902 or Qwen3.7 Max?

Qwen3.8 Max 0902 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.

Can I switch between Qwen3.8 Max 0902 and Qwen3.7 Max without rebuilding my integration?

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.

Can I try Qwen3.8 Max 0902 and Qwen3.7 Max in the browser before integrating?

Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.