Commercial Qwen3-VL tier for OCR, document parsing, video understanding and GUI-agent tasks with a toggleable thinking mode.
Modality:
Text
Image
model ID
qwen/qwen3-vl-plus
Output Speed *
N/A
tok/s
Intelligence Index *
N/A
/ 100
Context Window *
262144
tokens
Input price
0.9
Anytoken
Output price
2.46
Anytoken
Qwen3 VL Plus: A Vision-Language API for Documents, Video and Visual Agents
Qwen3 VL Plus is the commercial, closed-weight tier of Alibaba's Qwen3-VL vision-language series, served through Alibaba Cloud Model Studio. It accepts text, images and video and returns text, with a 262,144-token context window and a per-request toggleable thinking mode. It sits between the lightweight Flash tier and the open-weight 235B flagship, targeting teams that need strong OCR, multi-page document parsing, long-video understanding and GUI-agent capability behind a managed, OpenAI-compatible API rather than self-hosted weights. Document-heavy and screen-automation workloads benefit most.
Start sending document and video requests to Qwen3 VL Plus through the AnyAPI.ai endpoint.
Performance
Where Qwen3 VL Plus Concentrates Its Strength: Documents and Screens
Qwen3 VL Plus is built for reading and reasoning over visual content rather than pure text chat. Its strongest evidence is document intelligence: on the independent IDP Leaderboard the model scores 80.1% overall across OCR, table extraction, key-information extraction and visual question answering. The broader Qwen3-VL series reports OCR support across 32 languages above 70% accuracy and reliable long-video retrieval within its native context. For production, this means structured extraction from invoices, forms, charts and multi-page PDFs is a realistic primary use case, with the thinking mode available for harder reasoning steps.
Benchmarks
Independent Document and Multimodal Evidence for Qwen3 VL Plus
On the independent IDP Leaderboard, Qwen3-VL-Plus reaches 80.1% overall and ranks #10, spanning OCR, table extraction, key-information extraction and VQA — a directly model-specific signal for document workloads. Series-level results from the Qwen3-VL technical report (measured on open-weight variants, not this API tier) show strong image-math and OCR performance, with the 235B model trailing GPT-5 on the harder MMMU-Pro test. Treat series numbers as indicative of family capability rather than exact scores for the commercial Plus endpoint.
Output Speed
*
N/A
tok/s
Intelligence Index
*
N/A
/ 100
MMLU *
Broad world knowledge and problem-solving
0
%
GPQA *
PhD-level scientific reasoning across physics, biology, chemistry.
0
%
HLE *
Adherence to multi-step structured instructions.
0
%
LiveCodeBench *
Tool-calling reliability in long agentic loops.
0
%
Technical Specifications
What the model supports
Qwen3 VL Plus accepts text, image and video input and returns text. It exposes a 262,144-token context window and up to 32,768 output tokens, with a per-request enable_thinking toggle and thinking_budget control. Two specifications matter most in production: the video-plus-document context lets you feed long PDFs or extended footage in a single request, while visual tokens from images and video count toward input, so image-heavy prompts consume context and billing faster than text-only calls. The endpoint is OpenAI-compatible through Alibaba Cloud Model Studio.
Verified Specifications —
Qwen3 VL Plus
*
Input modalities
Text
Image
output modalities
Text
Context window
262144
tokens
Maximum output tokens
32768
Reasoning
Yes
Knowledge cutoff
September 2025
Pricing (standard)
0.9
AnyTokens in
/
2.46
AnyTokens out
Limitations & Trade-offs
1
Series benchmarks are not Plus-specific. Most published Qwen3-VL scores (MMMU, MathVision, OSWorld, ScreenSpot) come from the open-weight 2B–235B variants in the technical report, not the commercial qwen3-vl-plus endpoint. Only the IDP Leaderboard result (80.1% overall) is measured on this exact API tier. When capability is critical, validate on your own data rather than assuming the flagship's numbers transfer to Plus.
2
Visual tokens inflate context and cost. Images and video frames count toward input tokens, and pricing is tiered by input size per request. A single long video or a batch of high-resolution pages can push a request into a higher pricing bracket and consume large portions of the 262,144-token window, so image-heavy pipelines need token budgeting that text-only apps can skip.
3
Closed weights, no self-hosting for this tier. Unlike the open-weight Qwen3-VL models (2B through 235B) that you can run on vLLM or Transformers, qwen3-vl-plus is a managed commercial endpoint. Teams needing on-premises deployment, data residency beyond the available regional endpoints, or fine-tuning should evaluate the open-weight variants instead.
4
Text-only output and lags on the hardest reasoning. Qwen3 VL Plus returns text only — no image, audio or video generation. On the toughest multimodal reasoning tests such as MMMU-Pro, even the 235B flagship trails GPT-5, so for frontier general reasoning rather than document and screen understanding, a top-tier competitor may still be preferable.
Best-Fit Workloads
Where this model earns its place
01
Document and invoice extraction
The model's independent 80.1% IDP Leaderboard result spans OCR, table extraction and key-information extraction, making it a strong fit for turning invoices, forms and receipts into structured JSON. Combined with a 262,144-token context, it can process multi-page PDFs in a single request. Enable thinking for ambiguous layouts; keep it off for clean scans to save latency and tokens.
02
Long-video and footage analysis
The Qwen3-VL series reports faithful long-video retrieval within its native context, with the flagship holding high needle-in-haystack accuracy on hours-long footage. Qwen3 VL Plus can summarize meetings, index footage by event, or answer questions about extended video. Because frames consume input tokens, budget context carefully and downsample where full-frame fidelity is not required.
03
GUI and screen automation agents
Qwen3-VL is designed to recognize GUI elements, understand controls and invoke tools, with series-level state-of-the-art results on OSWorld reported in the technical report. Qwen3 VL Plus, with tool calling and structured outputs, suits agents that read screenshots and drive PC or mobile interfaces. Validate grounding accuracy on your target UI, since agent scores were measured on open-weight variants.
04
Chart and scientific-figure understanding
The series shows strong chart-description and reasoning performance on benchmarks like CharXiv and ChartQA. Qwen3 VL Plus fits analytics pipelines that extract values from charts, interpret dashboards, or answer questions about scientific figures. Use the thinking mode for multi-step quantitative reasoning over dense visuals; disable it for simple label or value reads.
Integration
01
One API integration
02
Easy model switching
03
Flexible for production
04