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Alibaba (Qwen)

Qwen 3.7 Plus

Frontier

Alibaba (Qwen)Released on 2026-06-02

Alibaba's cost-effective tier of the Qwen3.7 series, released June 2, 2026 on the Bailian platform. Unlike the text-only Qwen3.7-Max, Plus is multimodal — accepting text, image and video input — with a 1M-token context window (up to 256K reserved for chain-of-thought), deep reasoning, tool invocation and autonomous iteration. Priced ~60% below Qwen3.7-Max at $0.40/$1.60 per MTok. API-only on DashScope/Bailian — no open weights.

86
Overall Score

Voice of the community

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.

Qwen / OpenRouter model card2026-06-02

Alibaba's Qwen3.7-Plus supports text, video and imagery inputs at low cost of $0.4/$1.6 per 1M token — but it's proprietary.

VentureBeat2026-06-02

The clear shift in Qwen3.7 is its agentic focus, positioning the models for long-running tasks, with the Plus tier adding vision, deep reasoning and tool invocation at ~60% lower cost than Max.

MarkTechPost2026-06-02

Core Specs

1000K
Context Window
66K
Max Output
ReasoningOpen Sourcetextimagevideo

Pros & Cons

Sentiment50% +50% ·0% −

Pros

  • +Multimodal — accepts text, image and video input
  • +1M-token context with up to 256K reserved for reasoning
  • +Very low API pricing for a frontier multimodal model ($0.40/$1.60 per MTok)
  • +Agent-centric: tool invocation and autonomous iteration

Cons

  • API-only — no open weights
  • Independent benchmark verification still limited at launch
  • Performance claims largely vendor-reported
  • China-domiciled API (DashScope/Bailian) may concern some users

Pricing

Input (per 1M tokens)$0.40
Output (per 1M tokens)$1.60
Updated on 2026-06-03

Get Started

1Visit the provider's website
2Create an account
3Start using the model

Benchmarks

noteVendor-positioned as a cost-effective multimodal upgrade over Qwen3.7-Max, adding vision (image + video) input, deep reasoning, tool invocation and autonomous iteration. Allocates up to 256K tokens for internal chain-of-thought. Independent benchmark verification still pending.%

Reliability

Incidents (30d)0
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