import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "alibaba/qwen3.7-max", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "alibaba/qwen3.7-max", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"alibaba/qwen3.7-max","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| LiveCodeBench | 83.6% | Contamination-free competitive programming problems | Source | July 12, 2026 |
| Terminal-Bench | 69.7% | Autonomous shell/terminal task completion | Source | July 12, 2026 |
| SWE-bench Verified | 80.4% | Resolving verified real GitHub issues | Source | July 12, 2026 |
| GPQA Diamond | 92.4% | Google-proof graduate science questions (hardest subset) | Source | July 12, 2026 |
| Intelligence | 29.9 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Coding | 66 | Composite score across standardised coding evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Qwen 3.7 Max This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Qwen 3.7 Max has a 1,000,000 tokens context window and can return up to 65,536 tokens.
Qwen 3.7 Max takes text as input and returns text.
Use alibaba/qwen3.7-max as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Qwen 3.7 Max became available on May 21, 2026.
Qwen 3.7 Max is priced at input $2.6 / 1M tokens, output $7.8 / 1M tokens, cached input $2.6 / 1M tokens.
Yes, Qwen 3.7 Max can stream responses as they are generated.
Qwen 3.7 Max was built by Alibaba Cloud.
Yes, it supports function calling and tool use, including parallel tool calls.