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Qwen3.7 Plus
Qwen | 1,000,000 token context | $0.32/M input, $1.28/M output. Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its vision-language abilities while retaining full-stack, agent-level intelligence for coding, tool use, and productivity workflows. Its distinguishing trait is multi-modal interactive hybrid agent capability: it can perceive real-world scenes, read screens and interact with GUIs, generate code from visual references, and perform end-to-end navigation within mobile apps.
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Qwen3.7 Plus is a closed-weights multimodal model from Alibaba, sitting in the middle of the Qwen3.7 series on price and capability. Its headline feature is what Alibaba calls multi-modal interactive hybrid agent capability: it can read screens, interact with GUIs, navigate mobile apps end-to-end, and generate code from visual references. If your workflow involves vision-grounded agents or tool-heavy automation, this is the tier to look at.

Known for

  • Reads screens and interacts with GUIs as part of an agent loop
  • End-to-end mobile app navigation from visual input
  • Generates code from images or visual references
  • One-million-token context window for long document work
  • Priced below most frontier models at $0.32 input / $1.28 output per million tokens

Watch out for

  • Closed weights only — no local deployment, no self-hosting.
  • Vision-agent features depend on the API; not every integration will expose them.
  • Alibaba has not published a model card with benchmark details, so independent comparisons are thin.

Prompts to try

GUI agent task plan
I'm attaching a screenshot of a mobile app's home screen. Describe the exact sequence of taps and inputs needed to complete a new-user registration, naming each UI element you would interact with and flagging anything that looks like it could block automation.
Code from a wireframe
I'm attaching a hand-drawn wireframe of a two-column dashboard layout with a sidebar nav, a data table in the main area, and a filter bar at the top. Write the React component and Tailwind CSS classes that match this layout as closely as possible.
Long document extraction
Here is a 200-page technical specification. Extract every requirement that mentions a timeout value, format the results as a markdown table with columns: section number, requirement text, timeout value, and unit. Flag any rows where the unit is ambiguous.

Compare with

  • Qwen3.8 Flash
    Open-weights model
    1,000,000 token context · $0.15/M input, $0.47/M output
  • Qwen3.8 27B
    Open-weights model
    1,000,000 token context · $0.24/M input, $2.20/M output
  • Qwen3.6 35B A3B
    Open-weights model
    262,144 token context · $0.15/M input, $1.00/M output
  • Qwen3.5-9B
    Open-weights model
    262,144 token context · $0.10/M input, $0.15/M output
More text models from qwen

Questions people ask

Can I run Qwen3.7 Plus locally?
No. Qwen3.7 Plus is API-only with no open weights released, so local deployment is not possible.
What does Qwen3.7 Plus cost and how long is its context?
It costs $0.32 per million input tokens and $1.28 per million output tokens, with a one-million-token context window.
How does Qwen3.7 Plus differ from other models in the Qwen3.7 series?
Alibaba positions it as the cost-effective middle tier, with the distinguishing addition of vision-language and GUI-interaction capabilities layered on top of the series' core coding and agent strengths.
Captain's verdict
A genuinely useful pick if you need vision-grounded agents at a price that won't hurt — the GUI and mobile-navigation angle is rare at this cost.
Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.
Ranking badge
Updated Oct 22, 2026
Qwen3.7 Plus on ModelTrends.ai: Heat 5,473°
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How this score adds up
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Glossary: the terms used here
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One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor
The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents
Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale
Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes
Thumbs up and likes from every source, worth half a download each on the log scale.
Adoption rate
How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated
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Seeder
Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde
A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites
Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
OpenRouter tokens
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Full model (checkpoint)
The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
LoRA and embedding
Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
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Stand-in score
A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
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Typical model
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