Qwen: Qwen2.5-VL 7B Instruct

Qwen: Qwen2.5-VL 7B Instruct

qwen · Released Aug 28, 2024
Intelligence #479 / 688
27.6 our score
Speed
Not reported
Input Price #298 / 688
$0.200 per 1M tokens
Output Price #190 / 688
$0.200 per 1M tokens
Context #499 / 688
32,768 tokens

Analysis Summary

Qwen2.5-VL 7B Instruct is a compact multimodal model accepting text and images, with a 32K context window and low listed token pricing. Vision is its clearest operational advantage, opening use cases such as image classification, screenshot interpretation, product asset review, and lightweight document extraction. The supplied record does not include benchmark results, tool use, or function calling for this variant.

It is a sensible candidate for high-volume visual preprocessing, content tagging, and simple marketing asset workflows where cost matters and a human or downstream system checks results. The smaller model size and limited context make it less suitable for nuanced strategy, long-form client content, complex visual reasoning, or autonomous agents. Design for Online would consider it as a budget vision component, subject to a representative image and extraction test before deployment.

Assessed August 9, 2026

Editorial notes

Qwen2.5-VL 7B adds vision to a low-cost 7B model, making it useful for image and document extraction, while its 32K context and lack of supplied benchmarks limit confidence for complex work.

Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?

DFO Verdict

Qwen2.5-VL 7B adds vision to a low-cost 7B model, making it useful for image and document extraction, while its 32K context and lack of supplied benchmarks limit confidence for complex work.

#479 of 688 overall Down 62 this week

How Qwen: Qwen2.5-VL 7B Instruct compares

Its 33K-token context window is larger than 27% of the models we list. At $0.20 per million input tokens it is cheaper than 57% of comparable models.

Position in the field
Intelligence: smarter than 30% of models #479
Price: cheaper than 57% of models #298
Context: larger than 27% of models #499
worst in fieldmedianbest in field
Price vs frontier peers · $ per 1M tokens
Qwen: Qwen2.5-VL 7B Instruct $0.20 in $0.20 out
Claude Opus 5 $5.00 in $25.00 out
Qwen: Qwen3.8 Max $2.00 in $6.00 out
Anthropic: Claude Fable 5 $10.00 in $50.00 out

Dark bar = input · light bar = output, scaled to the priciest peer.

Context window vs peers · tokens
Qwen: Qwen2.5-VL 7B Instruct 33K

1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.

Intelligence0Technical0Value7.5Content4
Performance profile

Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.

Compare shapes side-by-side →

Pricing

Token Type Cost per 1M tokens Cost per 1K tokens
Input $0.20 $0.000200
Output $0.20 $0.000200

What would Qwen: Qwen2.5-VL 7B Instruct cost your business?

Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.

A website chatbot handling around 100 customer conversations a day, a few short messages each.

3,000
One request is one message, email, draft or automation call.
1,200 tokens

$0/mo Qwen: Qwen2.5-VL 7B Instruct

Full calculator with 688 models → Price Calculator

DFO AI AUTOMATION

These numbers get smaller with the right architecture.

We route routine calls to cheap models and save Qwen: Qwen2.5-VL 7B Instruct for the hard ones. Most clients cut their estimate by 60-80%.

Talk to our team

About Qwen: Qwen2.5-VL 7B Instruct

Qwen2.5 VL 7B is a multimodal LLM from the Qwen Team with the following key enhancements: - SoTA understanding of images of various resolution & ratio: Qwen2.5-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc. - Understanding videos of 20min+: Qwen2.5-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc. - Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2.5-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions. - Multilingual Support: to serve global users, besides English and Chinese, Qwen2.5-VL now supports the understanding of texts in different languages inside images, including most European languages, Japanese, Korean, Arabic, Vietnamese, etc. For more details, see this blog post and GitHub repo. Usage of this model is subject to Tongyi Qianwen LICENSE AGREEMENT.

Frequently asked questions about Qwen: Qwen2.5-VL 7B Instruct

How much does Qwen: Qwen2.5-VL 7B Instruct cost?

Qwen: Qwen2.5-VL 7B Instruct costs $0.20 per million input tokens and $0.20 per million output tokens.

What is the context window of Qwen: Qwen2.5-VL 7B Instruct?

Qwen: Qwen2.5-VL 7B Instruct has a context window of 32,768 tokens (33K).

What can Qwen: Qwen2.5-VL 7B Instruct do?

Qwen: Qwen2.5-VL 7B Instruct supports image/vision input.

Who created Qwen: Qwen2.5-VL 7B Instruct?

Qwen: Qwen2.5-VL 7B Instruct is developed by Qwen and was released on August 28, 2024.

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