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Text Generation Model

Qwen3.7 Plus

Alibaba's cost-effective Qwen3.7 flagship combining strong text generation, upgraded vision-language understanding, and agent-level intelligence for coding, GUI interaction, and tool use.

Publisher Qwen
Type Text
Context Window 1,000,000 tokens
Training Data May 2026
Input $0.40/MTok
Output $1.60/MTok
Provider Alibaba Cloud
LARGE CONTEXTREASONING

Qwen3.7 Plus

**Qwen3.7-Plus** is the cost-effective flagship model in Alibaba's Qwen3.7 series, combining robust text generation with a comprehensively upgraded vision-language stack — all while preserving full-stack, agent-level intelligence for coding, tool use, and productivity workflows. ### Key Capabilities - **Multi-modal interactive hybrid agent**: Perceives real-world scenes, reads screens, interacts with GUIs, generates code from visual references, and performs end-to-end navigation within mobile apps - **Deep Thinking mode**: Optional chain-of-thought reasoning (up to 256K thinking tokens) for complex problem solving, toggled via the `enable_thinking` parameter - **Visual understanding**: Accepts image, text, and video inputs for rich multimodal comprehension - **Massive context**: 1M token context window with up to 991K input tokens (983K in thinking mode) and 64K output tokens - **Tooling & structure**: Supports function calling, structured output, web search, prefix continuation, context caching (implicit and explicit), and batch processing ### Best Use Cases Qwen3.7-Plus is well-suited for agentic workflows that mix text, vision, and tool use — including GUI automation, screen understanding, code generation from visual mockups, long-document analysis, and cost-sensitive production deployments that still demand frontier-grade multimodal reasoning. This version is functionally equivalent to the snapshot `qwen3.7-plus-2026-05-26`.

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Parameters & options

Max Temperature 2
Max Response Size 64,000 tokens
Deep Thinking Select

When enabled, the model performs an internal chain-of-thought reasoning process before producing its final answer. Improves quality on complex tasks but increases latency and token usage (up to 256K chain-of-thought tokens).

Default: false
DisabledEnabled

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