Qwen: Qwen Plus 0728

Qwen: Qwen Plus 0728

qwen · Released Sep 8, 2025
Intelligence #274 / 756
34.4 our score
Speed
Not reported
Input Price #401 / 779
$0.260 per 1M tokens
Output Price #371 / 779
$0.780 per 1M tokens
Context #132 / 779
1M tokens

Analysis Summary

Qwen Plus 0728 is a text-only model with a 1M-token context window, tool use, and function calling. Its pricing supports economical use across large documents, structured content operations, and repeated API workflows. The input contains no benchmark results, however, so its reasoning, coding, instruction following, and reliability cannot be compared confidently with measured alternatives.

It is a sensible candidate for SEO briefs, content restructuring, document classification, and other workflows where long context and low cost drive the decision. Function calling expands its usefulness beyond simple generation, but there is no evidence here of robust autonomous execution. Start with bounded tasks, automated checks, and human approval for client-facing output. It is a volume-oriented option rather than a proven flagship.

Assessed September 7, 2026

Editorial notes

Qwen Plus 0728 offers a 1M-token context, tool use, and function calling at low cost, making it a strong volume candidate, but the supplied data does not verify its production quality.

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

DFO Verdict

Qwen Plus 0728 offers a 1M-token context, tool use, and function calling at low cost, making it a strong volume candidate, but the supplied data does not verify its production quality.

#274 of 756 overall

How Qwen: Qwen Plus 0728 compares

Its 1M-token context window is larger than 83% of the models we list. At $0.26 per million input tokens it is cheaper than 49% of comparable models.

Position in the field
Intelligence: smarter than 64% of models #274
Price: cheaper than 49% of models #401
Context: larger than 83% of models #132
worst in fieldmedianbest in field
Price vs frontier peers · $ per 1M tokens
Qwen: Qwen Plus 0728 $0.26 in $0.78 out
OpenAI: GPT-6 Astra $10.00 in $50.00 out
Anthropic: Claude Fable 5.1 $10.00 in $50.00 out
Claude Opus 5 $5.00 in $25.00 out

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

Context window vs peers · tokens

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

Intelligence0Technical0Value8.3Content5.2
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 $0.26 $0.000260
Output $0.78 $0.000780

What would Qwen: Qwen Plus 0728 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: Qwen Plus 0728

Full calculator with 779 models → Price Calculator

DFO AI AUTOMATION

These numbers get smaller with the right architecture.

We route routine calls to cheap models and save Qwen: Qwen Plus 0728 for the hard ones. Most clients cut their estimate by 60-80%.

Talk to our team

About Qwen: Qwen Plus 0728

Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.

Frequently asked questions about Qwen: Qwen Plus 0728

How much does Qwen: Qwen Plus 0728 cost?

Qwen: Qwen Plus 0728 costs $0.26 per million input tokens and $0.78 per million output tokens.

What is the context window of Qwen: Qwen Plus 0728?

Qwen: Qwen Plus 0728 has a context window of 1,000,000 tokens (1M).

What can Qwen: Qwen Plus 0728 do?

Qwen: Qwen Plus 0728 supports tool use and function calling.

Who created Qwen: Qwen Plus 0728?

Qwen: Qwen Plus 0728 is developed by Qwen and was released on September 8, 2025.

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