# Qwen 3.6 Plus API

Alibaba's Qwen 3.6 Plus, through an OpenAI-compatible API. 2 providers quote it now, and each request goes to the offer with the lowest estimated charge that meets your rules.

- Providers compete for each request. The exchange ranks the offers that meet your rules by estimated charge. It fixes your maximum charge before the first token, and you pay for the tokens that the model uses.
- The OpenAI and Anthropic APIs. Use the OpenAI or Anthropic SDK that you have. Set the base URL and your key, and send qwen3.6-plus as the model.
- Your data rules. Send x-liquid-retention: none and only offers whose provider does not keep your content compete for the request.

## Facts

- Model name: qwen3.6-plus
- Maker: Alibaba
- Context window: 64K tokens
- Input price: $0.280 to $0.500 per million tokens
- Output price: $1.680 to $3.000 per million tokens
- Providers: 2 independent providers
- Regions: global

## Providers

- [RelayGPU](https://liquidinference.ai/providers/42a59421-ba42-47c5-9e79-b05429ad3b59.md): global, $0.280 input and $1.680 output per million tokens, $0.028 cache read per million tokens, 64K tokens of context
- [EmpirioLabs AI](https://liquidinference.ai/providers/4f49f07c-0d26-44bd-88a8-34f3f5fbd3b7.md): global, $0.500 input and $3.000 output per million tokens, $0.500 cache read per million tokens, 64K tokens of context

## Scores

- HLE: 27.8, #88 of 273
- GPQA: 88.2, #55 of 250
- AA-LCR: 78.3, #65 of 237
- Terminal-Bench Hard: 43.9, #20 of 166
- τ²-Bench: 97.7, #9 of 169
- IFBench: 75.2, #21 of 178

Scores: Artificial Analysis (https://artificialanalysis.ai/)

## Request

```sh
curl https://router.inference.ai.exchange/v1/chat/completions \
  -H "Authorization: Bearer $LIQUID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.6-plus",
    "messages": [{"role":"user","content":"Say hello."}]
  }'
```

## Questions

### What is Qwen 3.6 Plus?

Served by intent-router: each job goes to the cheapest healthy upstream for this model.

### How much does Qwen 3.6 Plus cost?

Offers now ask $0.280 to $0.500 per million input tokens and $1.680 to $3.000 per million output tokens. A job pays for the tokens it uses. The exchange picks the cheapest eligible offer.

### What is the context length of Qwen 3.6 Plus?

The largest offer takes 64,000 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message.

### What can Qwen 3.6 Plus do?

Its providers list Reasoning budget, Reasoning effort, JSON object, Log probabilities, Presence penalty, Repetition penalty, Seed, Stop sequences, Top-k sampling, Top-p sampling, Text, Tools.

### What inputs and outputs does Qwen 3.6 Plus support?

Text → Text.

### Which providers serve Qwen 3.6 Plus?

2 independent providers quote it now, with 2 offers. The table above ranks them by the cost of a typical job.

### How do I call Qwen 3.6 Plus?

Send "qwen3.6-plus" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client.

### When was Qwen 3.6 Plus listed?

The exchange first listed it on 10/8/2026. This is not its release date.

## Related pages

- [This page in a browser](https://liquidinference.ai/models/qwen3.6-plus)
- [Qwen 3 14B](https://liquidinference.ai/models/qwen3-14b.md)
- [Qwen 3.8 27B](https://liquidinference.ai/models/qwen3.8-27b.md)
- [Qwen 3 5 4B](https://liquidinference.ai/models/qwen3-5-4b.md)
- [Qwen 3.5 9B](https://liquidinference.ai/models/qwen3.5-9b.md)
- [Qwen 2.5 7B Instruct](https://liquidinference.ai/models/qwen2.5-7b-instruct.md)
- [Qwen 3.6 35B a3b](https://liquidinference.ai/models/qwen3.6-35b-a3b.md)
- [Set up a client](https://liquidinference.ai/connect/qwen3.6-plus)
- [All models](https://liquidinference.ai/models)
- [Providers](https://liquidinference.ai/providers.md)
- [Discover the best model for your budget](https://liquidinference.ai/discover)
- [Quickstart](https://liquidinference.ai/docs/quickstart.md)
- [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt)
- [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)