Qwen · Model guide

Qwen3.6 Plus

Q: What is Qwen3.6 Plus?

Qwen3.6 Plus is available on CrossModel as qwen/qwen3.6-plus. It has a 1M-token context window and can return up to 66K tokens per request.

Q: How much does Qwen3.6 Plus cost?

Currently $ 0.32 per 1M input tokens and $ 1.88 per 1M output tokens. Cached input is billed at $ 0.032 per 1M.

Q: Does Qwen3.6 Plus support tool calling and structured output?

Tool calling: Supported · Structured output (JSON): Supported · Image input: Supported · Streaming: Supported · Thinking mode: Supported

Q: Which endpoint do I call?

For text models, OpenAI Chat Completions (/v1/chat/completions), OpenAI Responses (/v1/responses) and Anthropic Messages (/v1/messages) all work — pick whichever your SDK already speaks.

Q: Can I try it without writing code?

Yes. Sign in and open the Playground on this page to chat with the model directly — no API key needed. Usage is billed from your wallet at the normal rate.

Compare

qwen/qwen3.6-plus

A balanced 1M-context multimodal Qwen model for coding, document work and multi-turn agents, combining optional reasoning, function calling, structured output, caching and built-in tools.

Modalities

Context

Max output

66K

Price / 1M tokens

$ 0.32in$ 1.88out

StreamingTool callingJSON outputImage inputThinking mode · can be turned off

What this model is good at

What the vendor positions it for, and which of our models to reach for instead.

VendorA balanced multimodal model for coding tools and general enterprise workloads.source

Best for

Long-context knowledge work · Its 1M context, multimodal inputs and tools suit large documents and sustained conversations.(vendor claim)source

Neighbouring models

qwen/qwen3.7-plussuccessor —Choose Qwen3.7 Plus for the current balanced generation.(vendor claim)source

Compare them side by side →

Pricing and billing

Tiered pricing: the rate changes once the input passes the threshold.

Price / 1M tokens by input size	Input < 256.0K	Input ≥ 256.0K
Input	$ 0.32	$ 1.25
Output	$ 1.88	$ 7.50
Cache read	$ 0.032	$ 0.12
Cache write	$ 0.40	$ 1.57

Estimate a request

Input tokens10,000

Output tokens2,000

Cache hit rate0%

At this input size you are on the Input < 256.0K tier.

$ 0.0070

Estimated cost per request

10.0K × $ 0.32
+ 2.0K × $ 1.88

≈ $ 6.96 per 1,000 requests

Capabilities and limits

What CrossModel guarantees across every route this model can take right now.

Context window: 1.0M tokens
Max output: 65.5K tokens
Input / output modalities: Text + Image + Video → Text
Streaming: Supported
Tool calling: Supported
Structured output (JSON): Supported
Image input: Supported
Thinking mode: Supported· can be turned off
Available endpoints: /v1/chat/completions · /v1/responses · /v1/messages

First-party sources:Specshelp.aliyun.comCapabilitieshelp.aliyun.com 1 help.aliyun.com 2

Published benchmarks

Scores the vendor reported, with the evaluation setup each one came from.

Agentic coding

Terminal-Bench 2.0
pass_rate·Qwen Team · 2026-04-02setup not fully disclosed
61.6%

Coding

SWE-Bench Pro
resolved_rate·Qwen Team · 2026-04-02setup not fully disclosed
56.6%
SWE-Bench Verified
resolved_rate·Qwen Team · 2026-04-02setup not fully disclosed
78.8%

Computer use

OSWorld Verified
success_rate·Qwen Team · 2026-04-02setup not fully disclosed
62.5%

Multimodal reasoning

MMMU Pro
accuracy·Qwen Team · 2026-04-02setup not fully disclosed
78.8%

Reasoning

Humanity's Last Exam (with tools)
accuracy·Qwen Team · 2026-04-02setup not fully disclosed
Official table labels this HLE w/ tool; tool set was not disclosed.
50.6%

Scientific reasoning

GPQA Diamond
accuracy·Qwen Team · 2026-04-02setup not fully disclosed
The official table labels this row GPQA.
90.4%

Tool use

MCPMark
score·Qwen Team · 2026-04-02setup not fully disclosed
48.2%

Vendor-reported numbers, not CrossModel measurements. Scores are only comparable when the benchmark version, metric and evaluation setup match, so nothing here is averaged or ranked.

Use it in your tools

Point the base URL at CrossModel and paste this model ID — every tool below has a setup guide.

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Open-source AI coding agent for VS Code

Codex

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OpenCode

Open-source terminal coding assistant

Zed

High-performance, AI-native code editor

Open WebUI

Open-source, self-hosted AI chat interface

Continue

Open-source AI coding assistant for VS Code & JetBrains

See all integration guides →

Frequently asked questions

What is Qwen3.6 Plus?

Qwen3.6 Plus is available on CrossModel as qwen/qwen3.6-plus. It has a 1M-token context window and can return up to 66K tokens per request.

How much does Qwen3.6 Plus cost?

Currently $ 0.32 per 1M input tokens and $ 1.88 per 1M output tokens. Cached input is billed at $ 0.032 per 1M.

Does Qwen3.6 Plus support tool calling and structured output?

Tool calling: Supported · Structured output (JSON): Supported · Image input: Supported · Streaming: Supported · Thinking mode: Supported

Which endpoint do I call?

For text models, OpenAI Chat Completions (/v1/chat/completions), OpenAI Responses (/v1/responses) and Anthropic Messages (/v1/messages) all work — pick whichever your SDK already speaks.

Can I try it without writing code?