Qwen: Qwen2.5 VL 72B Instruct

Qwen: Qwen2.5 VL 72B Instruct

qwen · Released Feb 1, 2025
Intelligence #432 / 650
25.9 our score
Speed
Not reported
Input Price #331 / 688
$0.250 per 1M tokens
Output Price #314 / 688
$0.750 per 1M tokens
Context #428 / 688
128,000 tokens

Analysis Summary

Qwen2.5 VL 72B Instruct is a vision-language model without independent intelligence or coding benchmarks available, making its reasoning capability difficult to assess against current alternatives.

It may be useful for basic image description or visual document tasks, but businesses should validate output quality carefully before relying on it for client-facing or accuracy-critical work.

Pricing and context window are moderate; better-documented multimodal models are likely a safer choice where verified performance matters.

Assessed July 25, 2026

Editorial notes

Qwen2.5 VL 72B Instruct adds vision support but has no published reasoning benchmarks, limiting confidence for demanding business use.

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

DFO Verdict

Qwen2.5 VL 72B Instruct adds vision support but has no published reasoning benchmarks, limiting confidence for demanding business use.

#432 of 650 overall

How Qwen: Qwen2.5 VL 72B Instruct compares

Its 128K-token context window is larger than 38% of the models we list. At $0.25 per million input tokens it is cheaper than 52% of comparable models.

Position in the field
Intelligence: smarter than 34% of models #432
Price: cheaper than 52% of models #331
Context: larger than 38% of models #428
worst in fieldmedianbest in field
Price vs frontier peers · $ per 1M tokens
Qwen: Qwen2.5 VL 72B Instruct $0.25 in $0.75 out
Anthropic: Claude Fable 5 $10.00 in $50.00 out
Claude Opus 5 $5.00 in $25.00 out
Anthropic: Claude Opus 4.8 $5.00 in $25.00 out

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

Context window vs peers · tokens
Qwen: Qwen2.5 VL 72B Instruct 128K

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

Intelligence0Technical0Value7.3Content4.5
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 $0.25 $0.000250
Output $0.75 $0.000750

What would Qwen: Qwen2.5 VL 72B 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 72B 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 72B Instruct for the hard ones. Most clients cut their estimate by 60-80%.

Talk to our team

About Qwen: Qwen2.5 VL 72B Instruct

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

Frequently asked questions about Qwen: Qwen2.5 VL 72B Instruct

How much does Qwen: Qwen2.5 VL 72B Instruct cost?

Qwen: Qwen2.5 VL 72B Instruct costs $0.25 per million input tokens and $0.75 per million output tokens.

What is the context window of Qwen: Qwen2.5 VL 72B Instruct?

Qwen: Qwen2.5 VL 72B Instruct has a context window of 128,000 tokens (128K).

What can Qwen: Qwen2.5 VL 72B Instruct do?

Qwen: Qwen2.5 VL 72B Instruct supports image/vision input.

Who created Qwen: Qwen2.5 VL 72B Instruct?

Qwen: Qwen2.5 VL 72B Instruct is developed by Qwen and was released on February 1, 2025.

© 2026 Design for Online Ltd. Registered in England and Wales No. 10328553. VAT Registered. Design for Online® and Forerunner® are registered trademarks.