Qwen2.5-VL: Models, Licenses, Setup and Current Status

Last verified: August 2, 2026. Qwen2.5-VL is a 2025 vision-language model family from the Qwen team. It accepts text, images, and video and generates text. It does not generate images or audio.

The family remains useful when you need downloadable checkpoints, but it is no longer Alibaba Cloud’s recommended hosted vision family for a new project. The official collection now includes 3B, 7B, 32B, and 72B Instruct checkpoints, and the license is not the same for every size.

Qwen2.5-VL at a glance

Question	Verified answer
What can it read?	Text, images, and video
What can it produce?	Text, including descriptions, extracted data, coordinates, and action suggestions
Official Instruct sizes	3B, 7B, 32B, and 72B
Downloadable weights?	Yes, from the official Qwen collection; license varies by size
Current hosted status	Legacy in Alibaba Cloud Model Studio; not recommended there for a new project
Default local context in the official cards	32,768 tokens; longer-context configuration needs separate validation

Official checkpoints and licenses

Do not describe the entire Qwen2.5-VL family as Apache 2.0. Check the license attached to the exact checkpoint before commercial use.

Checkpoint	License shown by Qwen	Practical note
Qwen2.5-VL-3B-Instruct	Qwen Research License	Research use; obtain separate permission for commercial use.
Qwen2.5-VL-7B-Instruct	Apache 2.0	The smallest Apache-licensed Instruct checkpoint in this family.
Qwen2.5-VL-32B-Instruct	Apache 2.0	Added after the original 3B, 7B, and 72B release.
Qwen2.5-VL-72B-Instruct	Qwen License Agreement	Includes additional terms; the published license addresses services above 100 million monthly active users.

The official Qwen2.5-VL collection also lists quantized variants. A quantized checkpoint can reduce memory use, but its accuracy, throughput, and supported kernels depend on the backend. We do not publish a universal VRAM figure because image resolution, video frames, context length, precision, KV cache, and runtime all change memory requirements.

What Qwen2.5-VL was designed to do

• OCR and document parsing: read text, layouts, tables, forms, and charts from images.
• Visual grounding: describe or return locations for objects and regions.
• Image and video question answering: reason over visual content together with a text prompt.
• UI-action planning: suggest coordinates or actions for an external agent.
• Structured extraction: produce JSON-like text when prompted, which your application must still parse and validate.

Qwen reported video understanding beyond one hour in its launch material. That is a developer-reported capability, not a result independently reproduced by this site. Real results depend on frame sampling, resolution, video duration, prompt design, and the inference backend.

Important capability boundaries

• It returns text; it is not an image generator, video generator, or speech model.
• A model-generated coordinate or UI action is a proposal. An external tool executes it, so permission checks and human confirmation remain necessary.
• Prompted JSON is not the same as a provider-enforced structured-output feature. Parse it and reject invalid data.
• OCR can fail on small text, unusual fonts, blur, handwriting, low contrast, or dense layouts. Verify high-impact fields against the source image.
• Model Studio’s hosted limits and a local Hugging Face checkpoint’s configuration are different. Never copy one service limit into the other environment.

Local checkpoint names versus hosted API IDs

Qwen uses different namespaces for downloadable weights and Alibaba Cloud services. For example, Qwen/Qwen2.5-VL-7B-Instruct is a Hugging Face checkpoint, while qwen2.5-vl-7b-instruct is a Model Studio service ID. They should not be used interchangeably in code.

# Downloadable checkpoint namespace
Qwen/Qwen2.5-VL-7B-Instruct

# Alibaba Cloud managed-service namespace
qwen2.5-vl-7b-instruct

For local use, start from the installation and inference example on the exact official model card. Pin the package versions after a successful test, then record the checkpoint revision, precision, quantization, GPU, input dimensions, frame count, generation settings, and output. The official cards default to a 32,768-token configuration. Qwen warns that YaRN-based extension can affect temporal and spatial localization, so longer context needs its own acceptance tests.

Hosted status and migration

Alibaba Cloud’s current vision-model documentation places Qwen2.5-VL under legacy models and recommends newer services for new applications. Its current recommendation is qwen3.7-plus; qwen3.6-flash is a lower-cost option to evaluate after testing your own workload.

1. Keep the old model and the candidate replacement in the same provider region during comparison.
2. Build a small, permission-cleared image/video set that represents your production inputs.
3. Score OCR fields, object locations, refusal behavior, JSON validity, latency, and cost separately.
4. Do not send images to a replacement until its exact model card confirms visual input.
5. Pin a dated model or checkpoint revision when reproducibility matters.

Our verification method and test limits

We cross-checked the official Qwen collection, the four checkpoint licenses, Qwen’s launch post, and Alibaba Cloud’s current hosted-model catalog on August 2, 2026. A logged-in Model Studio session displayed the current catalog, but inference was unavailable because the account required additional business information (BASIC_INFO_UNCOMPLETED). No local GPU runtime for these checkpoints was available in this review. We therefore report no live output, benchmark, latency, or accuracy result for Qwen2.5-VL.

This is an explicit test boundary, not evidence that the model succeeds or fails. For a reproducible visual test, record the exact checkpoint or API ID, provider, region, date, prompt, original image, preprocessing, generation settings, raw output, and evaluation rule.

When to use Qwen2.5-VL

Choose Qwen2.5-VL when you specifically need a downloadable Qwen vision-language checkpoint and its size-specific license fits your project. For a new managed API integration, begin with Alibaba’s current vision recommendation instead. Compare other current and historical families in our Qwen models directory, or see the local download guide before choosing a checkpoint.

Official sources

• Qwen team: Qwen2.5-VL launch
• Official Qwen2.5-VL model collection
• Official Qwen2.5-VL repository
• Alibaba Cloud Model Studio vision models